In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data Found celeba Data
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
<matplotlib.image.AxesImage at 0x1bc9e135630>
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
<matplotlib.image.AxesImage at 0x1bc9e30cba8>
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.
The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).
You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputsdiscriminatorgeneratormodel_lossmodel_opttrainThis will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.0.1 Default GPU Device: /gpu:0
Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width, image_height, and image_channels.z_dim.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
import importlib
importlib.reload(tests)
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
inputs_real = tf.placeholder(tf.float32, [None, image_width, image_height, image_channels], name='input_real')
inputs_z = tf.placeholder(tf.float32, [None, z_dim], name='input_z')
learning_rate = tf.placeholder(tf.float32, name='learning_rate')
return inputs_real, inputs_z, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed
Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the generator, tensor logits of the generator).
def lrelu(tensor, alpha=0.2):
"""
Leaky ReLU implementation
:param tensor: Input Tensor
:param alpha: Leak scaling for negative inputs
:return: Leaky ReLU output
"""
return tf.maximum(tensor * alpha, tensor)
def discriminator(images, reuse=False, alpha=0.2, training=True):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
Optional
:param alpha: Leak factor for Leaky ReLU
:param training: Boolean for batch normalization to use batch or population statistics
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
# input is 28x28x1 or 28x28x3
with tf.variable_scope('discriminator', reuse=reuse):
x = tf.layers.conv2d(images, filters=64, kernel_size=5, strides=2, padding='same', activation=None)
x = lrelu(x, alpha)
# Now 14x14x64
# 2 conv layers for 7x7x128 -> 4x4x256
for filter_depth in [128, 256]:
x = tf.layers.conv2d(x, filters=filter_depth, kernel_size=5, strides=2, padding='same', activation=None, use_bias=False)
# Use batch normalization
x = tf.layers.batch_normalization(x, training=training)
x = lrelu(x, alpha)
# Now 4x4x256
flat = tf.reshape(x, [-1, 4*4*256])
logits = tf.layers.dense(flat, 1, activation=None)
out = tf.sigmoid(logits)
#print(x.shape, flat.shape, logits.shape)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed
Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.
def generator(z, out_channel_dim, is_train=True, alpha=0.2):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
Optional
:param alpha: Leak factor for Leaky ReLU
:return: The tensor output of the generator
"""
# TODO: Implement Function
# during training, don't reuse, during generation, reuse variables
with tf.variable_scope('generator', reuse=not is_train):
# Fully connected layer
x = tf.layers.dense(z, 2*2*1024, activation=None, use_bias=False)
# Reshape to start the conv stack
x = tf.reshape(x, (-1, 2, 2, 1024))
x = lrelu(x, alpha)
# Now 2x2x1024
x = tf.layers.conv2d_transpose(x, 512, kernel_size=5, strides=2, padding='valid', activation=None, use_bias=False)
x = tf.layers.batch_normalization(x, training=is_train)
x = lrelu(x, alpha)
# 7x7x512
#print(x.shape)
x = tf.layers.conv2d_transpose(x, 256, kernel_size=5, strides=2, padding='same', activation=None, use_bias=False)
x = tf.layers.batch_normalization(x, training=is_train)
x = lrelu(x, alpha)
# 14x14x256
#print(x.shape)
logits = tf.layers.conv2d_transpose(x, out_channel_dim, kernel_size=5, strides=2, padding='same')
# 28x28xout_channel_dim
#print(logits.shape)
# the real images from get_batches are scaled between -0.5 and 0.5
#scale = 0.5
#out = tf.multiply(tf.tanh(logits), scale)
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed
Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)generator(z, out_channel_dim, is_train=True)def model_loss(input_real, input_z, out_channel_dim, alpha=0.2, label_smooth=0.1):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
Optional
:param alpha: Leak factor for Leaky ReLU
:param label_smooth: Label smoothing for better discriminator generalization
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim, alpha=alpha)
d_model_real, d_logits_real = discriminator(input_real, alpha=alpha)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True, alpha=alpha)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real) * (1 - label_smooth)))
d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed
Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
# Get weights and bias
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
# Get batch normalization variables to update
d_update_opts = tf.get_collection(tf.GraphKeys.UPDATE_OPS, scope='discriminator')
g_update_opts = tf.get_collection(tf.GraphKeys.UPDATE_OPS, scope='generator')
with tf.control_dependencies(d_update_opts):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
with tf.control_dependencies(g_update_opts):
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)model_loss(input_real, input_z, out_channel_dim)model_opt(d_loss, g_loss, learning_rate, beta1)Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.
try:
from tqdm import tqdm
except ImportError:
def tqdm(x):
return x
!mkdir checkpoints
A subdirectory or file checkpoints already exists.
def plot_losses(losses):
"""
Plot training losses
:param losses: list of tuples of (discriminator loss, generator loss)
"""
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
# each row in losses is (discriminator loss, generator loss)
losses = np.array(losses)
# transpose of losses would give all discriminator losses as first row and generator losses as second row
plt.plot(losses.T[0], label='Discriminator', alpha=0.3)
plt.plot(losses.T[1], label='Generator')
plt.title('Training Losses')
plt.legend()
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode, alpha=0.2,
print_every=10, show_every=100, show_n_images=25):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
Optional
:param alpha: Leak factor for Leaky ReLU
:param print_every: Print loss every n steps
:param show_every: Show images generated every n steps
:param show_n_images: Number of images to show each time
"""
# TODO: Build Model
# data_shape is (samples x width x height x channels)
input_real, input_z, learn_rate = model_inputs(*data_shape[1:], z_dim)
out_channel_dim = data_shape[-1]
d_loss, g_loss = model_loss(input_real, input_z, out_channel_dim, alpha=alpha)
d_opt, g_opt = model_opt(d_loss, g_loss, learn_rate, beta1)
saver = tf.train.Saver()
steps = 0
losses = []
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
epoch_pbar = tqdm(range(epoch_count), desc='Epochs', unit='epoch')
#for epoch_i in range(epoch_count):
for epoch_i in epoch_pbar:
batch_count = data_shape[0]//batch_size
batch_pbar = tqdm(get_batches(batch_size), desc='Batches', unit='batch', miniters=show_every,
total=batch_count, maxinterval=360)
batch_i = 0
#for batch_images in get_batches(batch_size):
for batch_images in batch_pbar:
# TODO: Train Model
steps += 1
batch_i += 1
# the real images from get_batches are scaled between -0.5 and 0.5, so we scale to -1 to 1 to match generator
batch_images *= 2
# Sample random noise for Generator
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run optimizers
_ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, learn_rate: learning_rate})
# Train generator twice to meet loss lower than discriminator requirement
_ = sess.run(g_opt, feed_dict={input_z: batch_z, learn_rate: learning_rate})
_ = sess.run(g_opt, feed_dict={input_z: batch_z, learn_rate: learning_rate})
if steps % print_every == 0:
train_loss_d = d_loss.eval({input_real: batch_images, input_z: batch_z})
train_loss_g = g_loss.eval({input_z: batch_z})
print('Epoch {}/{}...'.format(epoch_i, epoch_count),
'Batch {}/{}...'.format(batch_i, batch_count),
'Discriminator loss: {:.4f}'.format(train_loss_d),
'Generator loss: {:.4f}'.format(train_loss_g))
losses.append((train_loss_d, train_loss_g))
if steps % show_every == 0:
show_generator_output(sess, show_n_images, input_z, out_channel_dim, data_image_mode)
saver.save(sess, './checkpoints/generator_bs{}_zd{}_lr{}_b{}.ckpt'.format(batch_size, z_dim, learning_rate, beta1))
plot_losses(losses)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
mnist_dataset.shape
(60000, 28, 28, 1)
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
celeba_dataset.shape
(202599, 28, 28, 3)
batch_size = 128
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode, alpha)
Epochs: 0%| | 0/2 [00:00<?, ?epoch/s] Batches: 0%| | 0/468 [00:00<?, ?batch/s]
Epoch 0/2... Batch 10/468... Discriminator loss: 0.4917 Generator loss: 5.2180 Epoch 0/2... Batch 20/468... Discriminator loss: 3.6643 Generator loss: 0.0700 Epoch 0/2... Batch 30/468... Discriminator loss: 2.1145 Generator loss: 3.2754 Epoch 0/2... Batch 40/468... Discriminator loss: 1.9406 Generator loss: 1.6231 Epoch 0/2... Batch 50/468... Discriminator loss: 0.8335 Generator loss: 1.9555 Epoch 0/2... Batch 60/468... Discriminator loss: 1.3331 Generator loss: 0.9221 Epoch 0/2... Batch 70/468... Discriminator loss: 1.4760 Generator loss: 0.5973 Epoch 0/2... Batch 80/468... Discriminator loss: 0.9745 Generator loss: 2.3600 Epoch 0/2... Batch 90/468... Discriminator loss: 0.8449 Generator loss: 1.4911 Epoch 0/2... Batch 100/468... Discriminator loss: 0.8251 Generator loss: 1.5158
Batches: 21%|███████████████▊ | 100/468 [00:26<01:38, 3.73batch/s]
Epoch 0/2... Batch 110/468... Discriminator loss: 1.2290 Generator loss: 1.7586 Epoch 0/2... Batch 120/468... Discriminator loss: 1.5158 Generator loss: 0.6855 Epoch 0/2... Batch 130/468... Discriminator loss: 1.6074 Generator loss: 0.9875 Epoch 0/2... Batch 140/468... Discriminator loss: 2.0240 Generator loss: 0.3558 Epoch 0/2... Batch 150/468... Discriminator loss: 0.9545 Generator loss: 1.3825 Epoch 0/2... Batch 160/468... Discriminator loss: 1.1279 Generator loss: 1.2117 Epoch 0/2... Batch 170/468... Discriminator loss: 1.1458 Generator loss: 1.0389 Epoch 0/2... Batch 180/468... Discriminator loss: 1.1388 Generator loss: 1.1487 Epoch 0/2... Batch 190/468... Discriminator loss: 1.2500 Generator loss: 1.3857 Epoch 0/2... Batch 200/468... Discriminator loss: 1.7996 Generator loss: 0.7772
Batches: 43%|███████████████████████████████▌ | 200/468 [00:52<01:10, 3.80batch/s]
Epoch 0/2... Batch 210/468... Discriminator loss: 1.2502 Generator loss: 0.8111 Epoch 0/2... Batch 220/468... Discriminator loss: 1.1672 Generator loss: 1.0612 Epoch 0/2... Batch 230/468... Discriminator loss: 1.4713 Generator loss: 0.8002 Epoch 0/2... Batch 240/468... Discriminator loss: 1.1337 Generator loss: 1.2037 Epoch 0/2... Batch 250/468... Discriminator loss: 1.2027 Generator loss: 1.0628 Epoch 0/2... Batch 260/468... Discriminator loss: 1.2021 Generator loss: 1.3674 Epoch 0/2... Batch 270/468... Discriminator loss: 1.4274 Generator loss: 0.6277 Epoch 0/2... Batch 280/468... Discriminator loss: 1.2764 Generator loss: 1.0985 Epoch 0/2... Batch 290/468... Discriminator loss: 1.1557 Generator loss: 1.0927 Epoch 0/2... Batch 300/468... Discriminator loss: 1.2954 Generator loss: 0.8428
Batches: 64%|███████████████████████████████████████████████▍ | 300/468 [01:19<00:44, 3.75batch/s]
Epoch 0/2... Batch 310/468... Discriminator loss: 1.3570 Generator loss: 1.0544 Epoch 0/2... Batch 320/468... Discriminator loss: 1.3732 Generator loss: 1.0085 Epoch 0/2... Batch 330/468... Discriminator loss: 1.3976 Generator loss: 1.1268 Epoch 0/2... Batch 340/468... Discriminator loss: 1.3836 Generator loss: 1.1496 Epoch 0/2... Batch 350/468... Discriminator loss: 1.2577 Generator loss: 1.3831 Epoch 0/2... Batch 360/468... Discriminator loss: 1.4038 Generator loss: 0.8038 Epoch 0/2... Batch 370/468... Discriminator loss: 1.4000 Generator loss: 1.0657 Epoch 0/2... Batch 380/468... Discriminator loss: 1.2514 Generator loss: 0.8665 Epoch 0/2... Batch 390/468... Discriminator loss: 1.4491 Generator loss: 0.6437 Epoch 0/2... Batch 400/468... Discriminator loss: 1.2428 Generator loss: 0.9599
Batches: 85%|███████████████████████████████████████████████████████████████▏ | 400/468 [01:44<00:17, 3.82batch/s]
Epoch 0/2... Batch 410/468... Discriminator loss: 1.4123 Generator loss: 1.3603 Epoch 0/2... Batch 420/468... Discriminator loss: 1.4848 Generator loss: 0.4702 Epoch 0/2... Batch 430/468... Discriminator loss: 1.3709 Generator loss: 0.9749 Epoch 0/2... Batch 440/468... Discriminator loss: 1.3116 Generator loss: 1.0834 Epoch 0/2... Batch 450/468... Discriminator loss: 1.2400 Generator loss: 1.0020 Epoch 0/2... Batch 460/468... Discriminator loss: 1.2240 Generator loss: 1.1380
Epochs: 50%|███████████████████████████████████████ | 1/2 [02:01<02:01, 121.09s/epoch] Batches: 0%| | 0/468 [00:00<?, ?batch/s]
Epoch 1/2... Batch 2/468... Discriminator loss: 1.3871 Generator loss: 0.7944 Epoch 1/2... Batch 12/468... Discriminator loss: 1.2662 Generator loss: 0.7959 Epoch 1/2... Batch 22/468... Discriminator loss: 1.3655 Generator loss: 0.6302 Epoch 1/2... Batch 32/468... Discriminator loss: 1.4927 Generator loss: 0.9913
Epoch 1/2... Batch 42/468... Discriminator loss: 1.2931 Generator loss: 0.7734 Epoch 1/2... Batch 52/468... Discriminator loss: 1.3677 Generator loss: 0.6417 Epoch 1/2... Batch 62/468... Discriminator loss: 1.4126 Generator loss: 0.6299 Epoch 1/2... Batch 72/468... Discriminator loss: 1.3792 Generator loss: 0.6583 Epoch 1/2... Batch 82/468... Discriminator loss: 1.3868 Generator loss: 0.8547 Epoch 1/2... Batch 92/468... Discriminator loss: 1.2090 Generator loss: 0.9803
Batches: 21%|███████████████▊ | 100/468 [00:24<01:31, 4.02batch/s]
Epoch 1/2... Batch 102/468... Discriminator loss: 1.3643 Generator loss: 0.9544 Epoch 1/2... Batch 112/468... Discriminator loss: 1.3566 Generator loss: 0.9705 Epoch 1/2... Batch 122/468... Discriminator loss: 1.3685 Generator loss: 0.8042 Epoch 1/2... Batch 132/468... Discriminator loss: 1.2974 Generator loss: 1.1905
Epoch 1/2... Batch 142/468... Discriminator loss: 1.3170 Generator loss: 0.6889 Epoch 1/2... Batch 152/468... Discriminator loss: 1.2391 Generator loss: 0.8194 Epoch 1/2... Batch 162/468... Discriminator loss: 1.4350 Generator loss: 0.9195 Epoch 1/2... Batch 172/468... Discriminator loss: 1.4016 Generator loss: 0.6460 Epoch 1/2... Batch 182/468... Discriminator loss: 1.3350 Generator loss: 0.6979 Epoch 1/2... Batch 192/468... Discriminator loss: 1.4232 Generator loss: 0.8011
Batches: 43%|███████████████████████████████▌ | 200/468 [00:49<01:06, 4.04batch/s]
Epoch 1/2... Batch 202/468... Discriminator loss: 1.5059 Generator loss: 1.2567 Epoch 1/2... Batch 212/468... Discriminator loss: 1.3714 Generator loss: 0.9867 Epoch 1/2... Batch 222/468... Discriminator loss: 1.3557 Generator loss: 1.4190 Epoch 1/2... Batch 232/468... Discriminator loss: 1.3524 Generator loss: 0.9505
Epoch 1/2... Batch 242/468... Discriminator loss: 1.4540 Generator loss: 0.6657 Epoch 1/2... Batch 252/468... Discriminator loss: 1.3012 Generator loss: 1.1714 Epoch 1/2... Batch 262/468... Discriminator loss: 1.4659 Generator loss: 0.8659 Epoch 1/2... Batch 272/468... Discriminator loss: 1.3775 Generator loss: 1.1010 Epoch 1/2... Batch 282/468... Discriminator loss: 1.2365 Generator loss: 0.8836 Epoch 1/2... Batch 292/468... Discriminator loss: 1.3333 Generator loss: 0.8778
Batches: 64%|███████████████████████████████████████████████▍ | 300/468 [01:14<00:41, 4.03batch/s]
Epoch 1/2... Batch 302/468... Discriminator loss: 1.2817 Generator loss: 1.0011 Epoch 1/2... Batch 312/468... Discriminator loss: 1.4207 Generator loss: 1.0578 Epoch 1/2... Batch 322/468... Discriminator loss: 1.4541 Generator loss: 0.5665 Epoch 1/2... Batch 332/468... Discriminator loss: 1.3423 Generator loss: 0.7892
Epoch 1/2... Batch 342/468... Discriminator loss: 1.3868 Generator loss: 0.6084 Epoch 1/2... Batch 352/468... Discriminator loss: 1.3785 Generator loss: 1.1364 Epoch 1/2... Batch 362/468... Discriminator loss: 1.3157 Generator loss: 0.7466 Epoch 1/2... Batch 372/468... Discriminator loss: 1.4727 Generator loss: 1.4169 Epoch 1/2... Batch 382/468... Discriminator loss: 1.4244 Generator loss: 0.7485 Epoch 1/2... Batch 392/468... Discriminator loss: 1.3714 Generator loss: 0.9000
Batches: 85%|███████████████████████████████████████████████████████████████▏ | 400/468 [01:40<00:17, 3.96batch/s]
Epoch 1/2... Batch 402/468... Discriminator loss: 1.4589 Generator loss: 1.1114 Epoch 1/2... Batch 412/468... Discriminator loss: 1.3919 Generator loss: 1.0841 Epoch 1/2... Batch 422/468... Discriminator loss: 1.4290 Generator loss: 0.5822 Epoch 1/2... Batch 432/468... Discriminator loss: 1.4165 Generator loss: 1.2199
Epoch 1/2... Batch 442/468... Discriminator loss: 1.3519 Generator loss: 0.7808 Epoch 1/2... Batch 452/468... Discriminator loss: 1.3349 Generator loss: 0.8850 Epoch 1/2... Batch 462/468... Discriminator loss: 1.3478 Generator loss: 0.7168
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 2/2 [04:00<00:00, 120.68s/epoch]
batch_size = 128
z_dim = 200
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode, alpha)
Epochs: 0%| | 0/2 [00:00<?, ?epoch/s] Batches: 0%| | 0/468 [00:00<?, ?batch/s]
Epoch 0/2... Batch 10/468... Discriminator loss: 0.4435 Generator loss: 10.7345 Epoch 0/2... Batch 20/468... Discriminator loss: 0.6819 Generator loss: 6.3631 Epoch 0/2... Batch 30/468... Discriminator loss: 2.0784 Generator loss: 0.2784 Epoch 0/2... Batch 40/468... Discriminator loss: 1.5113 Generator loss: 0.5470 Epoch 0/2... Batch 50/468... Discriminator loss: 1.9211 Generator loss: 2.1227 Epoch 0/2... Batch 60/468... Discriminator loss: 1.6089 Generator loss: 1.6311 Epoch 0/2... Batch 70/468... Discriminator loss: 1.1816 Generator loss: 2.3494 Epoch 0/2... Batch 80/468... Discriminator loss: 0.7240 Generator loss: 2.5696 Epoch 0/2... Batch 90/468... Discriminator loss: 1.6865 Generator loss: 2.2101 Epoch 0/2... Batch 100/468... Discriminator loss: 1.0282 Generator loss: 2.3086
Batches: 21%|███████████████▊ | 100/468 [00:50<03:05, 1.98batch/s]
Epoch 0/2... Batch 110/468... Discriminator loss: 1.0414 Generator loss: 2.3266 Epoch 0/2... Batch 120/468... Discriminator loss: 0.8370 Generator loss: 1.2102 Epoch 0/2... Batch 130/468... Discriminator loss: 0.8832 Generator loss: 1.4083 Epoch 0/2... Batch 140/468... Discriminator loss: 1.0062 Generator loss: 3.5232 Epoch 0/2... Batch 150/468... Discriminator loss: 1.4988 Generator loss: 0.5457 Epoch 0/2... Batch 160/468... Discriminator loss: 1.2900 Generator loss: 1.2644 Epoch 0/2... Batch 170/468... Discriminator loss: 0.8047 Generator loss: 1.4298 Epoch 0/2... Batch 180/468... Discriminator loss: 1.2491 Generator loss: 0.8524 Epoch 0/2... Batch 190/468... Discriminator loss: 1.5369 Generator loss: 3.5946 Epoch 0/2... Batch 200/468... Discriminator loss: 1.2011 Generator loss: 1.0701
Batches: 43%|███████████████████████████████▌ | 200/468 [01:36<02:11, 2.03batch/s]
Epoch 0/2... Batch 210/468... Discriminator loss: 1.1852 Generator loss: 0.9097 Epoch 0/2... Batch 220/468... Discriminator loss: 1.2709 Generator loss: 1.9000 Epoch 0/2... Batch 230/468... Discriminator loss: 1.5873 Generator loss: 0.6840 Epoch 0/2... Batch 240/468... Discriminator loss: 0.9993 Generator loss: 1.4596 Epoch 0/2... Batch 250/468... Discriminator loss: 1.2687 Generator loss: 1.4305 Epoch 0/2... Batch 260/468... Discriminator loss: 1.1471 Generator loss: 1.2122 Epoch 0/2... Batch 270/468... Discriminator loss: 1.0257 Generator loss: 1.2598 Epoch 0/2... Batch 280/468... Discriminator loss: 1.0547 Generator loss: 1.1313 Epoch 0/2... Batch 290/468... Discriminator loss: 1.3830 Generator loss: 0.6868 Epoch 0/2... Batch 300/468... Discriminator loss: 0.9425 Generator loss: 1.2102
Batches: 64%|███████████████████████████████████████████████▍ | 300/468 [02:24<01:21, 2.05batch/s]
Epoch 0/2... Batch 310/468... Discriminator loss: 1.3713 Generator loss: 1.1332 Epoch 0/2... Batch 320/468... Discriminator loss: 1.1907 Generator loss: 1.0091 Epoch 0/2... Batch 330/468... Discriminator loss: 1.4063 Generator loss: 1.2298 Epoch 0/2... Batch 340/468... Discriminator loss: 1.6128 Generator loss: 1.0067 Epoch 0/2... Batch 350/468... Discriminator loss: 1.5502 Generator loss: 0.8953 Epoch 0/2... Batch 360/468... Discriminator loss: 1.4479 Generator loss: 1.0112 Epoch 0/2... Batch 370/468... Discriminator loss: 1.1682 Generator loss: 1.5175 Epoch 0/2... Batch 380/468... Discriminator loss: 1.3367 Generator loss: 0.8333 Epoch 0/2... Batch 390/468... Discriminator loss: 1.3867 Generator loss: 1.1652 Epoch 0/2... Batch 400/468... Discriminator loss: 1.3632 Generator loss: 1.0347
Batches: 85%|███████████████████████████████████████████████████████████████▏ | 400/468 [03:13<00:33, 2.05batch/s]
Epoch 0/2... Batch 410/468... Discriminator loss: 1.3535 Generator loss: 1.2404 Epoch 0/2... Batch 420/468... Discriminator loss: 1.7433 Generator loss: 0.3725 Epoch 0/2... Batch 430/468... Discriminator loss: 1.4140 Generator loss: 1.2692 Epoch 0/2... Batch 440/468... Discriminator loss: 1.3175 Generator loss: 0.8893 Epoch 0/2... Batch 450/468... Discriminator loss: 1.3028 Generator loss: 0.9682 Epoch 0/2... Batch 460/468... Discriminator loss: 1.2309 Generator loss: 1.0571
Epochs: 50%|███████████████████████████████████████ | 1/2 [03:46<03:46, 226.36s/epoch] Batches: 0%| | 0/468 [00:00<?, ?batch/s]
Epoch 1/2... Batch 2/468... Discriminator loss: 1.3587 Generator loss: 0.6758 Epoch 1/2... Batch 12/468... Discriminator loss: 1.2621 Generator loss: 0.8704 Epoch 1/2... Batch 22/468... Discriminator loss: 1.2539 Generator loss: 1.0465 Epoch 1/2... Batch 32/468... Discriminator loss: 1.3647 Generator loss: 0.6363
Epoch 1/2... Batch 42/468... Discriminator loss: 1.3266 Generator loss: 0.7088 Epoch 1/2... Batch 52/468... Discriminator loss: 1.4700 Generator loss: 0.5024 Epoch 1/2... Batch 62/468... Discriminator loss: 1.3791 Generator loss: 0.9320 Epoch 1/2... Batch 72/468... Discriminator loss: 1.2789 Generator loss: 0.7328 Epoch 1/2... Batch 82/468... Discriminator loss: 1.4500 Generator loss: 0.8968 Epoch 1/2... Batch 92/468... Discriminator loss: 1.2438 Generator loss: 0.9133
Batches: 21%|███████████████▊ | 100/468 [00:25<01:32, 3.97batch/s]
Epoch 1/2... Batch 102/468... Discriminator loss: 1.3111 Generator loss: 1.0705 Epoch 1/2... Batch 112/468... Discriminator loss: 1.3884 Generator loss: 1.3091 Epoch 1/2... Batch 122/468... Discriminator loss: 1.4374 Generator loss: 0.7862 Epoch 1/2... Batch 132/468... Discriminator loss: 1.6408 Generator loss: 0.4247
Epoch 1/2... Batch 142/468... Discriminator loss: 1.3992 Generator loss: 1.1587 Epoch 1/2... Batch 152/468... Discriminator loss: 1.2317 Generator loss: 0.8792 Epoch 1/2... Batch 162/468... Discriminator loss: 1.3237 Generator loss: 0.8866 Epoch 1/2... Batch 172/468... Discriminator loss: 1.3876 Generator loss: 0.6790 Epoch 1/2... Batch 182/468... Discriminator loss: 1.4227 Generator loss: 1.0679 Epoch 1/2... Batch 192/468... Discriminator loss: 1.4026 Generator loss: 0.6883
Batches: 43%|███████████████████████████████▌ | 200/468 [00:49<01:07, 3.99batch/s]
Epoch 1/2... Batch 202/468... Discriminator loss: 1.3960 Generator loss: 1.0398 Epoch 1/2... Batch 212/468... Discriminator loss: 1.3786 Generator loss: 0.7405 Epoch 1/2... Batch 222/468... Discriminator loss: 1.2789 Generator loss: 0.7547 Epoch 1/2... Batch 232/468... Discriminator loss: 1.3206 Generator loss: 0.7819
Epoch 1/2... Batch 242/468... Discriminator loss: 1.4169 Generator loss: 0.6331 Epoch 1/2... Batch 252/468... Discriminator loss: 1.2402 Generator loss: 1.0589 Epoch 1/2... Batch 262/468... Discriminator loss: 1.3947 Generator loss: 0.9656 Epoch 1/2... Batch 272/468... Discriminator loss: 1.2891 Generator loss: 1.2145 Epoch 1/2... Batch 282/468... Discriminator loss: 1.1983 Generator loss: 0.9905 Epoch 1/2... Batch 292/468... Discriminator loss: 1.3305 Generator loss: 0.9516
Batches: 64%|███████████████████████████████████████████████▍ | 300/468 [01:15<00:42, 3.99batch/s]
Epoch 1/2... Batch 302/468... Discriminator loss: 1.2572 Generator loss: 0.7917 Epoch 1/2... Batch 312/468... Discriminator loss: 1.4530 Generator loss: 0.5764 Epoch 1/2... Batch 322/468... Discriminator loss: 1.4206 Generator loss: 0.6058 Epoch 1/2... Batch 332/468... Discriminator loss: 1.3564 Generator loss: 0.8770
Epoch 1/2... Batch 342/468... Discriminator loss: 1.3475 Generator loss: 0.7495 Epoch 1/2... Batch 352/468... Discriminator loss: 1.5035 Generator loss: 1.3818 Epoch 1/2... Batch 362/468... Discriminator loss: 1.3239 Generator loss: 0.9159 Epoch 1/2... Batch 372/468... Discriminator loss: 1.4482 Generator loss: 1.1449 Epoch 1/2... Batch 382/468... Discriminator loss: 1.3423 Generator loss: 0.8676 Epoch 1/2... Batch 392/468... Discriminator loss: 1.4075 Generator loss: 0.8432
Batches: 85%|███████████████████████████████████████████████████████████████▏ | 400/468 [01:40<00:17, 3.99batch/s]
Epoch 1/2... Batch 402/468... Discriminator loss: 1.4808 Generator loss: 1.1490 Epoch 1/2... Batch 412/468... Discriminator loss: 1.3945 Generator loss: 1.1055 Epoch 1/2... Batch 422/468... Discriminator loss: 1.6173 Generator loss: 0.4040 Epoch 1/2... Batch 432/468... Discriminator loss: 1.3005 Generator loss: 0.7706
Epoch 1/2... Batch 442/468... Discriminator loss: 1.4244 Generator loss: 0.6941 Epoch 1/2... Batch 452/468... Discriminator loss: 1.2694 Generator loss: 0.8146 Epoch 1/2... Batch 462/468... Discriminator loss: 1.3219 Generator loss: 0.7451
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 2/2 [05:43<00:00, 193.61s/epoch]
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 128
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
# Generator Losses seem ok, but faces generated are bad
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
batch_size = 64
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
# Generator Losses seem ok, but faces generated are bad
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
batch_size = 32
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
# Generator Losses seem ok, but faces generated are bad
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
batch_size = 32
z_dim = 200 # Try doubling from earlier attempt of 100
learning_rate = 0.0005
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
batch_size = 256
z_dim = 200
learning_rate = 0.01 # too high
beta1 = 0.5
alpha = 0.2
# Generator Losses jumping around too much. Batch size and learning rate seem too high to be stable. Faces are too noisy
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/791 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/791... Discriminator loss: 3.4570 Generator loss: 0.1437 Epoch 0/1... Batch 20/791... Discriminator loss: 2.4284 Generator loss: 3.3371 Epoch 0/1... Batch 30/791... Discriminator loss: 0.6787 Generator loss: 5.0026 Epoch 0/1... Batch 40/791... Discriminator loss: 1.2642 Generator loss: 6.0321 Epoch 0/1... Batch 50/791... Discriminator loss: 2.6873 Generator loss: 1.6424 Epoch 0/1... Batch 60/791... Discriminator loss: 0.6704 Generator loss: 2.7082 Epoch 0/1... Batch 70/791... Discriminator loss: 1.0521 Generator loss: 2.3508 Epoch 0/1... Batch 80/791... Discriminator loss: 1.3881 Generator loss: 1.0394 Epoch 0/1... Batch 90/791... Discriminator loss: 0.6054 Generator loss: 2.5848 Epoch 0/1... Batch 100/791... Discriminator loss: 0.5554 Generator loss: 1.8850
Batches: 13%|█████████▎ | 100/791 [02:05<14:24, 1.25s/batch]
Epoch 0/1... Batch 110/791... Discriminator loss: 0.4814 Generator loss: 3.1759 Epoch 0/1... Batch 120/791... Discriminator loss: 0.3945 Generator loss: 4.0385 Epoch 0/1... Batch 130/791... Discriminator loss: 0.9977 Generator loss: 1.0179 Epoch 0/1... Batch 140/791... Discriminator loss: 1.0327 Generator loss: 1.8289 Epoch 0/1... Batch 150/791... Discriminator loss: 1.0169 Generator loss: 1.8406 Epoch 0/1... Batch 160/791... Discriminator loss: 0.6310 Generator loss: 2.2822 Epoch 0/1... Batch 170/791... Discriminator loss: 1.0231 Generator loss: 1.4359 Epoch 0/1... Batch 180/791... Discriminator loss: 0.7165 Generator loss: 1.8134 Epoch 0/1... Batch 190/791... Discriminator loss: 0.4087 Generator loss: 3.2192 Epoch 0/1... Batch 200/791... Discriminator loss: 0.3802 Generator loss: 3.9742
Batches: 25%|██████████████████▋ | 200/791 [04:05<12:10, 1.24s/batch]
Epoch 0/1... Batch 210/791... Discriminator loss: 0.3910 Generator loss: 3.1805 Epoch 0/1... Batch 220/791... Discriminator loss: 0.3506 Generator loss: 4.3192 Epoch 0/1... Batch 230/791... Discriminator loss: 0.4349 Generator loss: 4.6078 Epoch 0/1... Batch 240/791... Discriminator loss: 0.3470 Generator loss: 4.2532 Epoch 0/1... Batch 250/791... Discriminator loss: 0.3636 Generator loss: 3.7173 Epoch 0/1... Batch 260/791... Discriminator loss: 0.3403 Generator loss: 4.6121 Epoch 0/1... Batch 270/791... Discriminator loss: 0.3348 Generator loss: 5.3991 Epoch 0/1... Batch 280/791... Discriminator loss: 0.3412 Generator loss: 5.8729 Epoch 0/1... Batch 290/791... Discriminator loss: 0.3323 Generator loss: 6.4463 Epoch 0/1... Batch 300/791... Discriminator loss: 0.3302 Generator loss: 6.1946
Batches: 38%|████████████████████████████ | 300/791 [06:10<10:09, 1.24s/batch]
Epoch 0/1... Batch 310/791... Discriminator loss: 0.3865 Generator loss: 9.5156 Epoch 0/1... Batch 320/791... Discriminator loss: 0.3643 Generator loss: 15.2904 Epoch 0/1... Batch 330/791... Discriminator loss: 0.3617 Generator loss: 4.7436 Epoch 0/1... Batch 340/791... Discriminator loss: 0.3428 Generator loss: 5.5071 Epoch 0/1... Batch 350/791... Discriminator loss: 0.3278 Generator loss: 10.2527 Epoch 0/1... Batch 360/791... Discriminator loss: 0.3459 Generator loss: 4.5914 Epoch 0/1... Batch 370/791... Discriminator loss: 0.3911 Generator loss: 4.5637 Epoch 0/1... Batch 380/791... Discriminator loss: 0.3335 Generator loss: 5.2410 Epoch 0/1... Batch 390/791... Discriminator loss: 0.4299 Generator loss: 8.5181 Epoch 0/1... Batch 400/791... Discriminator loss: 2.4820 Generator loss: 4.2033
Batches: 51%|█████████████████████████████████████▍ | 400/791 [07:20<07:01, 1.08s/batch]
Epoch 0/1... Batch 410/791... Discriminator loss: 1.9930 Generator loss: 0.9494 Epoch 0/1... Batch 420/791... Discriminator loss: 0.9337 Generator loss: 1.5956 Epoch 0/1... Batch 430/791... Discriminator loss: 1.4076 Generator loss: 1.1299 Epoch 0/1... Batch 440/791... Discriminator loss: 1.0554 Generator loss: 1.0217 Epoch 0/1... Batch 450/791... Discriminator loss: 1.2807 Generator loss: 1.0521 Epoch 0/1... Batch 460/791... Discriminator loss: 1.3113 Generator loss: 0.9976 Epoch 0/1... Batch 470/791... Discriminator loss: 1.7538 Generator loss: 1.4148 Epoch 0/1... Batch 480/791... Discriminator loss: 1.3521 Generator loss: 0.9649 Epoch 0/1... Batch 490/791... Discriminator loss: 1.2591 Generator loss: 0.6668 Epoch 0/1... Batch 500/791... Discriminator loss: 1.1729 Generator loss: 1.0440
Batches: 63%|██████████████████████████████████████████████▊ | 500/791 [08:37<04:47, 1.01batch/s]
Epoch 0/1... Batch 510/791... Discriminator loss: 1.2740 Generator loss: 0.7684 Epoch 0/1... Batch 520/791... Discriminator loss: 1.0771 Generator loss: 1.8000 Epoch 0/1... Batch 530/791... Discriminator loss: 1.1301 Generator loss: 1.1554 Epoch 0/1... Batch 540/791... Discriminator loss: 1.4479 Generator loss: 0.7528 Epoch 0/1... Batch 550/791... Discriminator loss: 1.6097 Generator loss: 1.0192 Epoch 0/1... Batch 560/791... Discriminator loss: 1.1949 Generator loss: 1.1047 Epoch 0/1... Batch 570/791... Discriminator loss: 1.8688 Generator loss: 2.2322 Epoch 0/1... Batch 580/791... Discriminator loss: 1.6142 Generator loss: 0.6179 Epoch 0/1... Batch 590/791... Discriminator loss: 1.4606 Generator loss: 0.8085 Epoch 0/1... Batch 600/791... Discriminator loss: 1.3407 Generator loss: 0.7972
Batches: 76%|████████████████████████████████████████████████████████▏ | 600/791 [10:37<03:20, 1.05s/batch]
Epoch 0/1... Batch 610/791... Discriminator loss: 1.3856 Generator loss: 0.8172 Epoch 0/1... Batch 620/791... Discriminator loss: 1.5665 Generator loss: 1.4348 Epoch 0/1... Batch 630/791... Discriminator loss: 1.2902 Generator loss: 1.0119 Epoch 0/1... Batch 640/791... Discriminator loss: 1.2913 Generator loss: 1.0471 Epoch 0/1... Batch 650/791... Discriminator loss: 1.3357 Generator loss: 1.7641 Epoch 0/1... Batch 660/791... Discriminator loss: 1.4572 Generator loss: 1.2197 Epoch 0/1... Batch 670/791... Discriminator loss: 1.5018 Generator loss: 1.1212 Epoch 0/1... Batch 680/791... Discriminator loss: 1.2784 Generator loss: 0.8738 Epoch 0/1... Batch 690/791... Discriminator loss: 1.4037 Generator loss: 0.7382 Epoch 0/1... Batch 700/791... Discriminator loss: 1.3033 Generator loss: 0.7524
Batches: 88%|█████████████████████████████████████████████████████████████████▍ | 700/791 [12:34<01:38, 1.08s/batch]
Epoch 0/1... Batch 710/791... Discriminator loss: 1.2799 Generator loss: 0.7301 Epoch 0/1... Batch 720/791... Discriminator loss: 1.4055 Generator loss: 0.7610 Epoch 0/1... Batch 730/791... Discriminator loss: 1.3408 Generator loss: 0.9486 Epoch 0/1... Batch 740/791... Discriminator loss: 1.4732 Generator loss: 0.7711 Epoch 0/1... Batch 750/791... Discriminator loss: 1.2626 Generator loss: 0.9075 Epoch 0/1... Batch 760/791... Discriminator loss: 1.2218 Generator loss: 0.8914 Epoch 0/1... Batch 770/791... Discriminator loss: 1.2315 Generator loss: 0.8463 Epoch 0/1... Batch 780/791... Discriminator loss: 1.5221 Generator loss: 1.1132 Epoch 0/1... Batch 790/791... Discriminator loss: 1.1568 Generator loss: 0.7930
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [14:27<00:00, 867.90s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.001
beta1 = 0.5
alpha = 0.2
# the visuals on batch 6300 randomly looks acceptable, but unable to get similar results on second run
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 0.5115 Generator loss: 3.7177 Epoch 0/1... Batch 20/6331... Discriminator loss: 1.4912 Generator loss: 1.4111 Epoch 0/1... Batch 30/6331... Discriminator loss: 1.7850 Generator loss: 0.8752 Epoch 0/1... Batch 40/6331... Discriminator loss: 1.9232 Generator loss: 0.5031 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.2939 Generator loss: 2.2244 Epoch 0/1... Batch 60/6331... Discriminator loss: 1.2366 Generator loss: 1.0862 Epoch 0/1... Batch 70/6331... Discriminator loss: 2.1008 Generator loss: 0.2211 Epoch 0/1... Batch 80/6331... Discriminator loss: 1.8862 Generator loss: 0.7034 Epoch 0/1... Batch 90/6331... Discriminator loss: 2.2137 Generator loss: 0.4439 Epoch 0/1... Batch 100/6331... Discriminator loss: 1.7722 Generator loss: 0.9343
Batches: 2%|█▏ | 100/6331 [00:14<14:59, 6.92batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 1.5820 Generator loss: 1.2259 Epoch 0/1... Batch 120/6331... Discriminator loss: 1.6295 Generator loss: 0.9286 Epoch 0/1... Batch 130/6331... Discriminator loss: 1.0056 Generator loss: 1.2434 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.9914 Generator loss: 0.3788 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.9521 Generator loss: 0.5895 Epoch 0/1... Batch 160/6331... Discriminator loss: 1.8908 Generator loss: 0.4599 Epoch 0/1... Batch 170/6331... Discriminator loss: 1.7976 Generator loss: 0.5415 Epoch 0/1... Batch 180/6331... Discriminator loss: 1.7391 Generator loss: 0.4484 Epoch 0/1... Batch 190/6331... Discriminator loss: 1.6702 Generator loss: 0.5741 Epoch 0/1... Batch 200/6331... Discriminator loss: 1.8568 Generator loss: 0.4284
Batches: 3%|██▎ | 200/6331 [00:28<14:35, 7.00batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.5538 Generator loss: 0.5793 Epoch 0/1... Batch 220/6331... Discriminator loss: 1.8365 Generator loss: 0.4889 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.6418 Generator loss: 0.6146 Epoch 0/1... Batch 240/6331... Discriminator loss: 2.0320 Generator loss: 0.3784 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.4182 Generator loss: 0.9006 Epoch 0/1... Batch 260/6331... Discriminator loss: 1.5828 Generator loss: 0.6806 Epoch 0/1... Batch 270/6331... Discriminator loss: 1.6587 Generator loss: 0.5697 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.3113 Generator loss: 0.8651 Epoch 0/1... Batch 290/6331... Discriminator loss: 1.5334 Generator loss: 0.6386 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.4307 Generator loss: 0.7520
Batches: 5%|███▍ | 300/6331 [00:41<14:00, 7.17batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.8979 Generator loss: 0.5056 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.5771 Generator loss: 0.7117 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.5796 Generator loss: 0.7230 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.6321 Generator loss: 0.6169 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.5606 Generator loss: 0.6677 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.7702 Generator loss: 0.6650 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.5790 Generator loss: 0.7038 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.4638 Generator loss: 0.7664 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.5293 Generator loss: 0.7090 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.5801 Generator loss: 0.6138
Batches: 6%|████▌ | 400/6331 [00:54<13:30, 7.31batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.7609 Generator loss: 0.6207 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.6922 Generator loss: 0.6316 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.6942 Generator loss: 0.6461 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.6414 Generator loss: 0.6087 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.6476 Generator loss: 0.6879 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.4302 Generator loss: 0.6643 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.5180 Generator loss: 0.7492 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.6794 Generator loss: 0.5900 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.4455 Generator loss: 0.7339 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.4423 Generator loss: 0.7312
Batches: 8%|█████▊ | 500/6331 [01:07<13:13, 7.35batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.5461 Generator loss: 0.6094 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.5828 Generator loss: 0.6297 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.4993 Generator loss: 0.7926 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.5523 Generator loss: 0.7590 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.5511 Generator loss: 0.7390 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.3548 Generator loss: 0.8218 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.4038 Generator loss: 0.7035 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.5500 Generator loss: 0.7442 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.5012 Generator loss: 0.7046 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.5114 Generator loss: 0.7587
Batches: 9%|██████▉ | 600/6331 [01:21<12:55, 7.39batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.4858 Generator loss: 0.7497 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.5102 Generator loss: 0.7621 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.4195 Generator loss: 0.8035 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.4353 Generator loss: 0.7575 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.5002 Generator loss: 0.8111 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.4159 Generator loss: 0.8595 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.4254 Generator loss: 0.6462 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.4827 Generator loss: 0.7059 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.4634 Generator loss: 0.7626 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.3053 Generator loss: 0.7935
Batches: 11%|████████ | 700/6331 [01:35<12:47, 7.33batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.4197 Generator loss: 0.8506 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.4818 Generator loss: 0.6683 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.3824 Generator loss: 0.7635 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.5430 Generator loss: 0.7215 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.4323 Generator loss: 0.7887 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.3281 Generator loss: 0.8785 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.3630 Generator loss: 0.8404 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.5107 Generator loss: 0.7190 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.4673 Generator loss: 0.7107 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.6098 Generator loss: 0.6687
Batches: 13%|█████████▏ | 800/6331 [01:48<12:24, 7.43batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.5027 Generator loss: 0.6197 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.5203 Generator loss: 0.7458 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.5218 Generator loss: 0.6887 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.4076 Generator loss: 0.7757 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.3456 Generator loss: 0.8066 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.4250 Generator loss: 0.7202 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.4575 Generator loss: 0.6826 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.3455 Generator loss: 0.8087 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.4844 Generator loss: 0.6533 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.4557 Generator loss: 0.8936
Batches: 14%|██████████▍ | 900/6331 [02:01<12:05, 7.49batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.4307 Generator loss: 0.7888 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.4431 Generator loss: 0.6561 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.5232 Generator loss: 0.6922 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.5819 Generator loss: 0.6832 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.3929 Generator loss: 0.7799 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.4755 Generator loss: 0.7390 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.4753 Generator loss: 0.6685 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.4142 Generator loss: 0.7800 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.3855 Generator loss: 0.7626 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.5207 Generator loss: 0.7318
Batches: 16%|███████████▎ | 1000/6331 [02:14<11:55, 7.45batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.3316 Generator loss: 0.7956 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.4104 Generator loss: 0.6639 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.5001 Generator loss: 0.6799 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.3970 Generator loss: 0.8744 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.4317 Generator loss: 0.7568 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.5774 Generator loss: 0.7784 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.5774 Generator loss: 0.9344 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.5618 Generator loss: 0.7179 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.5047 Generator loss: 0.7849 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.4877 Generator loss: 0.7700
Batches: 17%|████████████▌ | 1100/6331 [02:28<11:46, 7.40batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.4473 Generator loss: 0.7476 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.5909 Generator loss: 0.6391 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.4345 Generator loss: 0.7766 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.4996 Generator loss: 0.8295 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.3867 Generator loss: 0.8055 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.5432 Generator loss: 0.6405 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.4466 Generator loss: 0.7169 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.4081 Generator loss: 0.8599 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.4908 Generator loss: 0.8855 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.3317 Generator loss: 0.7257
Batches: 19%|█████████████▋ | 1200/6331 [02:42<11:33, 7.40batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.6198 Generator loss: 0.6814 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.4339 Generator loss: 0.7481 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.4611 Generator loss: 0.7509 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.4429 Generator loss: 0.7261 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.4163 Generator loss: 0.7190 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.3996 Generator loss: 0.7694 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.4770 Generator loss: 0.8288 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.5419 Generator loss: 0.7256 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.3928 Generator loss: 0.8494 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.3177 Generator loss: 0.8213
Batches: 21%|██████████████▊ | 1300/6331 [02:55<11:12, 7.48batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.3926 Generator loss: 0.7882 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.3892 Generator loss: 0.7434 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.4325 Generator loss: 0.7457 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.4444 Generator loss: 0.8771 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.4213 Generator loss: 0.7412 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.3957 Generator loss: 0.8960 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.5190 Generator loss: 0.6497 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.4081 Generator loss: 0.7073 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.4349 Generator loss: 0.7674 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.4809 Generator loss: 0.8030
Batches: 22%|███████████████▉ | 1400/6331 [03:08<10:54, 7.54batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.3659 Generator loss: 0.7795 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.4552 Generator loss: 0.8410 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.3530 Generator loss: 0.7698 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.4409 Generator loss: 0.6443 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4438 Generator loss: 0.7865 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.5233 Generator loss: 0.7912 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.5479 Generator loss: 0.5735 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.4904 Generator loss: 0.8310 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4506 Generator loss: 0.6569 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.4125 Generator loss: 0.6423
Batches: 24%|█████████████████ | 1500/6331 [03:21<10:37, 7.58batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.4347 Generator loss: 0.7550 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.4642 Generator loss: 0.6549 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.4747 Generator loss: 0.7166 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.4473 Generator loss: 0.8209 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.4694 Generator loss: 0.7615 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.4222 Generator loss: 0.7286 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.3752 Generator loss: 0.8192 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.5574 Generator loss: 0.6691 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.4623 Generator loss: 0.7325 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.4377 Generator loss: 0.7390
Batches: 25%|██████████████████▏ | 1600/6331 [03:35<10:35, 7.45batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.3858 Generator loss: 0.7584 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.4421 Generator loss: 0.7235 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.3913 Generator loss: 0.8516 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.3877 Generator loss: 0.8084 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.4517 Generator loss: 0.6736 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.4409 Generator loss: 0.8398 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4312 Generator loss: 0.8076 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.4482 Generator loss: 0.7622 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.4464 Generator loss: 0.7728 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.4925 Generator loss: 0.7081
Batches: 27%|███████████████████▎ | 1700/6331 [03:48<10:16, 7.51batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.5591 Generator loss: 0.7775 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.4785 Generator loss: 0.7310 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.5514 Generator loss: 0.6312 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.3874 Generator loss: 0.7589 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.3827 Generator loss: 0.8208 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.3898 Generator loss: 0.7681 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4094 Generator loss: 0.7054 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.4216 Generator loss: 0.8237 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.4110 Generator loss: 0.7237 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.4009 Generator loss: 0.7863
Batches: 28%|████████████████████▍ | 1800/6331 [04:01<10:01, 7.53batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.4644 Generator loss: 0.8004 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.4251 Generator loss: 0.7808 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.4372 Generator loss: 0.7736 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.4395 Generator loss: 0.7633 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.4487 Generator loss: 0.6806 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.4415 Generator loss: 0.7256 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.4412 Generator loss: 0.6931 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.3977 Generator loss: 0.8963 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.4627 Generator loss: 0.6524 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4993 Generator loss: 0.7575
Batches: 30%|█████████████████████▌ | 1900/6331 [04:14<09:46, 7.56batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.4785 Generator loss: 0.7254 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.4684 Generator loss: 0.7497 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.5416 Generator loss: 0.8361 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.4589 Generator loss: 0.6946 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.4097 Generator loss: 0.7226 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.5460 Generator loss: 0.9572 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.4350 Generator loss: 0.7298 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.3513 Generator loss: 0.7272 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.5630 Generator loss: 0.9798 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.5238 Generator loss: 0.7562
Batches: 32%|██████████████████████▋ | 2000/6331 [04:27<09:34, 7.55batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.4743 Generator loss: 0.6492 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.5159 Generator loss: 0.7213 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.4624 Generator loss: 0.7322 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.5657 Generator loss: 0.6855 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.5141 Generator loss: 0.6769 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4669 Generator loss: 0.7576 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.4981 Generator loss: 0.8398 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.5646 Generator loss: 0.8173 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.4728 Generator loss: 0.6964 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.5670 Generator loss: 0.6754
Batches: 33%|███████████████████████▉ | 2100/6331 [04:41<09:27, 7.46batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.4010 Generator loss: 0.8410 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.4024 Generator loss: 0.8484 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.4336 Generator loss: 0.7110 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.4355 Generator loss: 0.7709 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4677 Generator loss: 0.6776 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.3536 Generator loss: 0.7905 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.4297 Generator loss: 0.6736 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.3478 Generator loss: 0.7406 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.4611 Generator loss: 0.6773 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.4403 Generator loss: 0.7015
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Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.4569 Generator loss: 0.7453 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.3861 Generator loss: 0.8670 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.5040 Generator loss: 0.7448 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.4473 Generator loss: 0.7632 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.4081 Generator loss: 0.7140 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.4141 Generator loss: 0.7336 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.4337 Generator loss: 0.8051 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4536 Generator loss: 0.7305 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.4634 Generator loss: 0.9157 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.3940 Generator loss: 0.7486
Batches: 36%|██████████████████████████▏ | 2300/6331 [05:09<09:06, 7.37batch/s]
Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.4295 Generator loss: 0.8475 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.4791 Generator loss: 0.7901 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.3963 Generator loss: 0.8109 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.4644 Generator loss: 0.7084 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.3851 Generator loss: 0.7035 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.4080 Generator loss: 0.7413 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.4665 Generator loss: 0.7122 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.4060 Generator loss: 0.8535 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4748 Generator loss: 0.7641 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.4332 Generator loss: 0.6739
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Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.3752 Generator loss: 0.8534 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.5437 Generator loss: 0.6800 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.5281 Generator loss: 0.7776 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.4890 Generator loss: 0.6608 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.4567 Generator loss: 0.7753 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.4348 Generator loss: 0.7313 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.4061 Generator loss: 0.7490 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.3718 Generator loss: 0.9342 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.4065 Generator loss: 0.8218 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.4195 Generator loss: 0.8128
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Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.4318 Generator loss: 0.7665 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.4734 Generator loss: 0.6687 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.4447 Generator loss: 0.7500 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.4625 Generator loss: 0.7400 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.4143 Generator loss: 0.9831 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.4985 Generator loss: 0.8184 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.4212 Generator loss: 0.7469 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.4870 Generator loss: 0.5722 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.4239 Generator loss: 0.7539 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.4190 Generator loss: 0.7560
Batches: 41%|█████████████████████████████▌ | 2600/6331 [05:53<08:59, 6.91batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.4025 Generator loss: 0.7857 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.4376 Generator loss: 0.9321 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.4462 Generator loss: 0.8611 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.3794 Generator loss: 0.6725 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.5321 Generator loss: 0.7351 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.4501 Generator loss: 0.7286 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.4223 Generator loss: 0.8414 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.4517 Generator loss: 0.5713 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.3821 Generator loss: 0.7923 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.4010 Generator loss: 0.7394
Batches: 43%|██████████████████████████████▋ | 2700/6331 [06:07<08:42, 6.95batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.3928 Generator loss: 0.7885 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.3939 Generator loss: 0.9136 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.4708 Generator loss: 0.5700 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.5389 Generator loss: 0.5371 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.6984 Generator loss: 0.7033 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.4283 Generator loss: 0.8233 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.4112 Generator loss: 0.7972 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.3972 Generator loss: 0.6983 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.3746 Generator loss: 0.8133 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.3752 Generator loss: 0.7292
Batches: 44%|███████████████████████████████▊ | 2800/6331 [06:22<08:37, 6.83batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.3752 Generator loss: 0.9040 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.4096 Generator loss: 0.7668 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.4645 Generator loss: 0.7317 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.4139 Generator loss: 0.7036 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.3924 Generator loss: 0.8873 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.5617 Generator loss: 0.6605 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.5177 Generator loss: 0.6903 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4118 Generator loss: 0.8508 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.4751 Generator loss: 0.6774 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.4537 Generator loss: 0.6782
Batches: 46%|████████████████████████████████▉ | 2900/6331 [06:36<08:16, 6.91batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4161 Generator loss: 0.8592 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4717 Generator loss: 0.6258 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.4102 Generator loss: 0.7580 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.3946 Generator loss: 0.7517 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.4147 Generator loss: 0.7844 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.3757 Generator loss: 0.7912 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.4166 Generator loss: 0.9227 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.4170 Generator loss: 0.7511 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.4081 Generator loss: 0.8290 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.4258 Generator loss: 0.7906
Batches: 47%|██████████████████████████████████ | 3000/6331 [06:50<08:00, 6.94batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.4337 Generator loss: 0.6477 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.3910 Generator loss: 0.8487 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.4055 Generator loss: 0.8399 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.3665 Generator loss: 0.7965 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.4530 Generator loss: 0.7003 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.3817 Generator loss: 0.7605 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.4096 Generator loss: 0.7209 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.4097 Generator loss: 0.8184 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.3930 Generator loss: 0.8334 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.4171 Generator loss: 0.6820
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [07:05<07:44, 6.95batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.4201 Generator loss: 0.7893 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.5216 Generator loss: 0.7665 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4214 Generator loss: 0.7476 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.4736 Generator loss: 0.6555 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.4035 Generator loss: 0.6598 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.4056 Generator loss: 0.7347 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.3739 Generator loss: 0.8445 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.4247 Generator loss: 0.7232 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.4149 Generator loss: 0.8025 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4966 Generator loss: 0.7273
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [07:19<07:28, 6.98batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4197 Generator loss: 0.7636 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4684 Generator loss: 1.0071 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.4121 Generator loss: 0.7383 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.4583 Generator loss: 0.7206 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.3857 Generator loss: 0.7641 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.4451 Generator loss: 0.8213 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.4164 Generator loss: 0.6879 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.3236 Generator loss: 0.7756 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.4236 Generator loss: 0.8681 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.4329 Generator loss: 0.7949
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [07:33<07:14, 6.97batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.4265 Generator loss: 0.8407 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.3771 Generator loss: 0.8876 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.5096 Generator loss: 0.5977 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.4395 Generator loss: 0.6791 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4960 Generator loss: 0.6093 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.4319 Generator loss: 0.6198 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.4546 Generator loss: 0.8075 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.4343 Generator loss: 0.6530 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.3410 Generator loss: 0.7164 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.4019 Generator loss: 0.7802
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [07:48<07:07, 6.86batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.4083 Generator loss: 0.7255 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.4208 Generator loss: 0.7330 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.4127 Generator loss: 0.7511 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.4034 Generator loss: 0.7217 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3627 Generator loss: 0.8572 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.4576 Generator loss: 0.8141 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.4200 Generator loss: 0.6865 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.4392 Generator loss: 0.6701 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.3964 Generator loss: 0.8742 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.4168 Generator loss: 0.7976
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [08:02<06:46, 6.96batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.3941 Generator loss: 0.7261 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.3674 Generator loss: 0.7156 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.4278 Generator loss: 0.7290 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.4136 Generator loss: 0.8607 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.4071 Generator loss: 0.7345 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.4024 Generator loss: 0.8463 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.3995 Generator loss: 0.9113 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.4101 Generator loss: 0.6818 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.4023 Generator loss: 0.8163 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.4127 Generator loss: 0.7119
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [08:16<06:25, 7.08batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.4061 Generator loss: 0.7498 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.3981 Generator loss: 0.7625 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.5186 Generator loss: 0.7159 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.4133 Generator loss: 0.7122 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.4235 Generator loss: 0.9122 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.3834 Generator loss: 0.7108 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3861 Generator loss: 0.7473 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.3828 Generator loss: 0.7868 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.3984 Generator loss: 0.8501 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.4322 Generator loss: 0.6745
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [08:30<06:11, 7.08batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.4146 Generator loss: 0.7115 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.4017 Generator loss: 0.9070 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.4198 Generator loss: 0.7407 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.4369 Generator loss: 0.7331 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.4851 Generator loss: 0.5702 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.3963 Generator loss: 0.7441 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.4032 Generator loss: 0.6951 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.3962 Generator loss: 0.7997 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.3837 Generator loss: 0.8108 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.4007 Generator loss: 0.8684
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [08:44<05:57, 7.08batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.4264 Generator loss: 0.7798 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.4404 Generator loss: 0.6817 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.3943 Generator loss: 0.7610 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.3663 Generator loss: 1.0006 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.3976 Generator loss: 0.7162 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.4208 Generator loss: 0.7964 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.4380 Generator loss: 0.8012 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.3832 Generator loss: 0.8683 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.3871 Generator loss: 0.8532 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.4117 Generator loss: 0.7681
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [08:58<05:40, 7.13batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.3920 Generator loss: 0.8014 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.4179 Generator loss: 0.7205 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.4190 Generator loss: 0.7238 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.4163 Generator loss: 0.7334 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.4403 Generator loss: 0.8286 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.3967 Generator loss: 0.7937 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.4099 Generator loss: 0.7578 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.3675 Generator loss: 0.8573 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.3888 Generator loss: 0.7716 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.4045 Generator loss: 0.7261
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [09:11<05:23, 7.20batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.3934 Generator loss: 0.8268 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.4417 Generator loss: 0.8519 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.4382 Generator loss: 0.8521 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.4195 Generator loss: 0.7599 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.4383 Generator loss: 0.8339 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.4111 Generator loss: 0.8311 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.4503 Generator loss: 0.8605 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.3795 Generator loss: 0.7290 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.3869 Generator loss: 0.8939 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.3940 Generator loss: 0.7596
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [09:25<05:09, 7.20batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.3991 Generator loss: 0.7920 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.3881 Generator loss: 0.7679 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.4213 Generator loss: 0.7038 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.3757 Generator loss: 0.8679 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.4187 Generator loss: 0.9458 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.3864 Generator loss: 0.7981 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.4068 Generator loss: 0.7595 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.4071 Generator loss: 0.8917 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.4026 Generator loss: 0.8684 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.3808 Generator loss: 0.8904
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.3530 Generator loss: 0.7872 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.3800 Generator loss: 0.7435 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.3861 Generator loss: 0.7705 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.3962 Generator loss: 0.8993 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.3667 Generator loss: 0.7894 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.4074 Generator loss: 0.7576 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.4018 Generator loss: 0.8519 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.4012 Generator loss: 0.7174 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.3707 Generator loss: 0.7961 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.4189 Generator loss: 0.7428
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.4080 Generator loss: 0.7698 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.3700 Generator loss: 0.7319 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3868 Generator loss: 0.7534 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.4089 Generator loss: 0.7540 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.4147 Generator loss: 0.7253 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.4058 Generator loss: 0.7736 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.4134 Generator loss: 0.6390 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.4018 Generator loss: 0.7744 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.4035 Generator loss: 0.7792 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.3846 Generator loss: 0.8466
Batches: 71%|███████████████████████████████████████████████████▏ | 4500/6331 [10:24<04:24, 6.91batch/s]
Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.4094 Generator loss: 0.7643 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.3958 Generator loss: 0.9458 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.3979 Generator loss: 0.8085 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.3964 Generator loss: 0.7925 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.3780 Generator loss: 0.8174 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.3968 Generator loss: 0.7805 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.4033 Generator loss: 0.8518 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.3988 Generator loss: 0.7799 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.4080 Generator loss: 0.8457 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.4118 Generator loss: 0.7164
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Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.3949 Generator loss: 0.7817 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.3808 Generator loss: 0.7506 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.3913 Generator loss: 0.8388 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.4122 Generator loss: 0.7626 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.3871 Generator loss: 0.8340 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.4251 Generator loss: 0.7993 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.3842 Generator loss: 0.7612 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.4156 Generator loss: 0.7015 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.3967 Generator loss: 0.7697 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.4184 Generator loss: 0.7760
Batches: 74%|█████████████████████████████████████████████████████▍ | 4700/6331 [10:51<03:50, 7.08batch/s]
Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.3893 Generator loss: 0.7368 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3794 Generator loss: 0.8252 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3817 Generator loss: 0.7943 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.3714 Generator loss: 0.7621 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.3683 Generator loss: 0.8097 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.3980 Generator loss: 0.9143 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.4014 Generator loss: 0.7933 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.4056 Generator loss: 0.6788 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.4345 Generator loss: 0.6873 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.3987 Generator loss: 0.8495
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [11:05<03:34, 7.15batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.4145 Generator loss: 0.8420 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.4105 Generator loss: 0.7295 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.3958 Generator loss: 0.8017 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.3854 Generator loss: 0.7440 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.3907 Generator loss: 0.7680 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.4062 Generator loss: 0.8494 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3857 Generator loss: 0.7582 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.4024 Generator loss: 0.7021 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.3684 Generator loss: 0.8335 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.3896 Generator loss: 0.7761
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [11:18<03:16, 7.26batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.3968 Generator loss: 0.7158 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.3920 Generator loss: 0.8306 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.3891 Generator loss: 0.7639 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.3806 Generator loss: 0.7154 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.3834 Generator loss: 0.7713 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.4124 Generator loss: 0.8832 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.3950 Generator loss: 0.7874 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.3773 Generator loss: 0.8175 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.3778 Generator loss: 0.7855 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.4122 Generator loss: 0.8499
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [11:32<03:02, 7.29batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.3875 Generator loss: 0.8158 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.4275 Generator loss: 0.7752 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.3932 Generator loss: 0.7309 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.3846 Generator loss: 0.7550 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.3870 Generator loss: 0.7573 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.4278 Generator loss: 0.7414 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.3896 Generator loss: 0.8461 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.3962 Generator loss: 0.6980 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.3944 Generator loss: 0.7249 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.4020 Generator loss: 0.7823
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [11:46<02:48, 7.30batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.3749 Generator loss: 0.7938 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.4137 Generator loss: 0.6973 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.3998 Generator loss: 0.7429 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.4025 Generator loss: 0.7938 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.3907 Generator loss: 0.8267 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3917 Generator loss: 0.7588 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.4045 Generator loss: 0.8144 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.4069 Generator loss: 0.9357 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.4148 Generator loss: 0.6864 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.3923 Generator loss: 0.7962
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [12:00<02:36, 7.22batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.3783 Generator loss: 0.8141 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.3976 Generator loss: 0.7943 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.4003 Generator loss: 0.7358 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.4103 Generator loss: 0.7541 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.3883 Generator loss: 0.8240 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.3895 Generator loss: 0.8006 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.4036 Generator loss: 0.8263 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.3946 Generator loss: 0.7321 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.3947 Generator loss: 0.8120 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.4067 Generator loss: 0.7341
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [12:15<02:25, 7.08batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.4282 Generator loss: 0.8268 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3791 Generator loss: 0.8094 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3916 Generator loss: 0.7720 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.3959 Generator loss: 0.8569 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.3982 Generator loss: 0.7773 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.4047 Generator loss: 0.8038 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3972 Generator loss: 0.7386 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.3846 Generator loss: 0.7846 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3958 Generator loss: 0.8180 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.4043 Generator loss: 0.8135
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [12:28<02:09, 7.21batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3836 Generator loss: 0.7580 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3941 Generator loss: 0.8238 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3935 Generator loss: 0.6968 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3847 Generator loss: 0.8204 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.4156 Generator loss: 0.6133 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3972 Generator loss: 0.7184 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3916 Generator loss: 0.8681 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.3785 Generator loss: 0.7639 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.3890 Generator loss: 0.7918 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.3900 Generator loss: 0.8895
Batches: 87%|██████████████████████████████████████████████████████████████▌ | 5500/6331 [12:42<01:56, 7.12batch/s]
Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.4110 Generator loss: 0.8542 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3988 Generator loss: 0.8535 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3784 Generator loss: 0.7572 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.3716 Generator loss: 0.7816 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3691 Generator loss: 0.8011 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.3766 Generator loss: 0.8079 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3844 Generator loss: 0.7449 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.3783 Generator loss: 0.8334 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.3876 Generator loss: 0.7906 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.3878 Generator loss: 0.7896
Batches: 88%|███████████████████████████████████████████████████████████████▋ | 5600/6331 [12:58<01:45, 6.91batch/s]
Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.3821 Generator loss: 0.8539 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3954 Generator loss: 0.7534 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3987 Generator loss: 0.8495 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3853 Generator loss: 0.8129 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.4124 Generator loss: 0.6714 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3797 Generator loss: 0.8260 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3934 Generator loss: 0.8659 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.3717 Generator loss: 0.7703 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.4024 Generator loss: 0.8716 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3743 Generator loss: 0.8305
Batches: 90%|████████████████████████████████████████████████████████████████▊ | 5700/6331 [13:13<01:32, 6.82batch/s]
Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3931 Generator loss: 0.7462 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.4027 Generator loss: 0.8155 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.3971 Generator loss: 0.7740 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.3873 Generator loss: 0.8379 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.3997 Generator loss: 0.8360 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.3991 Generator loss: 0.7544 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.3808 Generator loss: 0.6986 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.4090 Generator loss: 0.7620 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3900 Generator loss: 0.7458 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.3880 Generator loss: 0.8171
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Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.3911 Generator loss: 0.8245 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.3787 Generator loss: 0.7938 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.4310 Generator loss: 0.6852 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.3909 Generator loss: 0.9091 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.3755 Generator loss: 0.7464 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.3968 Generator loss: 0.8719 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3972 Generator loss: 0.6480 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.3937 Generator loss: 0.8196 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.4120 Generator loss: 0.7340 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3913 Generator loss: 0.7720
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3826 Generator loss: 0.8237 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3907 Generator loss: 0.7308 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3733 Generator loss: 0.8341 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3943 Generator loss: 0.8509 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.3840 Generator loss: 0.7776 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.3858 Generator loss: 0.8106 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3759 Generator loss: 0.8611 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.4020 Generator loss: 0.7642 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.4086 Generator loss: 0.9277 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3771 Generator loss: 0.8464
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.3702 Generator loss: 0.8223 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3872 Generator loss: 0.7850 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3951 Generator loss: 0.7417 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.3664 Generator loss: 0.7687 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3934 Generator loss: 0.7593 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.4380 Generator loss: 0.8229 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.4070 Generator loss: 0.6733 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.4025 Generator loss: 0.7669 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.3870 Generator loss: 0.8564 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3999 Generator loss: 0.7373
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.4059 Generator loss: 0.7979 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.4033 Generator loss: 0.7269 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3948 Generator loss: 0.8672 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.3976 Generator loss: 0.8344 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.3948 Generator loss: 0.7317 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.3946 Generator loss: 0.7689 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.4003 Generator loss: 0.7544 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.3852 Generator loss: 0.7504 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3789 Generator loss: 0.8298 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3890 Generator loss: 0.7069
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [14:24<00:18, 6.93batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.3905 Generator loss: 0.6960 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3856 Generator loss: 0.7763 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3912 Generator loss: 0.6751 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3781 Generator loss: 0.7952 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.3757 Generator loss: 0.7971 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3939 Generator loss: 0.7445 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3869 Generator loss: 0.8083 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3830 Generator loss: 0.7983 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3817 Generator loss: 0.8186 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3894 Generator loss: 0.8088
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [14:38<00:04, 7.02batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.4049 Generator loss: 0.7546 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.3905 Generator loss: 0.8088 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3768 Generator loss: 0.7997
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [14:42<00:00, 882.69s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.001
beta1 = 0.5
alpha = 0.2
# unable to match the visuals of the previous run for some reason
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 0.5044 Generator loss: 4.1206 Epoch 0/1... Batch 20/6331... Discriminator loss: 2.5716 Generator loss: 1.7344 Epoch 0/1... Batch 30/6331... Discriminator loss: 1.3623 Generator loss: 2.3181 Epoch 0/1... Batch 40/6331... Discriminator loss: 1.1700 Generator loss: 2.5861 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.2700 Generator loss: 2.1419 Epoch 0/1... Batch 60/6331... Discriminator loss: 1.5807 Generator loss: 3.0621 Epoch 0/1... Batch 70/6331... Discriminator loss: 1.5137 Generator loss: 1.0864 Epoch 0/1... Batch 80/6331... Discriminator loss: 1.1109 Generator loss: 0.8963 Epoch 0/1... Batch 90/6331... Discriminator loss: 1.6350 Generator loss: 3.3098 Epoch 0/1... Batch 100/6331... Discriminator loss: 2.0212 Generator loss: 0.5976
Batches: 2%|█▏ | 100/6331 [00:14<14:46, 7.03batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 1.6211 Generator loss: 2.5513 Epoch 0/1... Batch 120/6331... Discriminator loss: 2.5464 Generator loss: 2.2082 Epoch 0/1... Batch 130/6331... Discriminator loss: 3.7240 Generator loss: 0.0723 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.4602 Generator loss: 0.5043 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.1416 Generator loss: 1.3309 Epoch 0/1... Batch 160/6331... Discriminator loss: 2.3332 Generator loss: 1.2819 Epoch 0/1... Batch 170/6331... Discriminator loss: 1.7067 Generator loss: 0.6473 Epoch 0/1... Batch 180/6331... Discriminator loss: 1.7837 Generator loss: 0.5620 Epoch 0/1... Batch 190/6331... Discriminator loss: 1.6740 Generator loss: 0.6191 Epoch 0/1... Batch 200/6331... Discriminator loss: 1.4184 Generator loss: 0.8758
Batches: 3%|██▎ | 200/6331 [00:27<14:07, 7.23batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.5115 Generator loss: 0.6955 Epoch 0/1... Batch 220/6331... Discriminator loss: 2.0329 Generator loss: 0.4020 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.3306 Generator loss: 0.8538 Epoch 0/1... Batch 240/6331... Discriminator loss: 1.4250 Generator loss: 0.9303 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.2684 Generator loss: 0.9046 Epoch 0/1... Batch 260/6331... Discriminator loss: 2.0126 Generator loss: 0.4926 Epoch 0/1... Batch 270/6331... Discriminator loss: 1.6497 Generator loss: 0.6497 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.6938 Generator loss: 0.7078 Epoch 0/1... Batch 290/6331... Discriminator loss: 1.6415 Generator loss: 0.6343 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.3235 Generator loss: 0.9469
Batches: 5%|███▍ | 300/6331 [00:40<13:36, 7.38batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.6571 Generator loss: 0.5934 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.6070 Generator loss: 0.5833 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.5757 Generator loss: 0.6724 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.5104 Generator loss: 0.9249 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.6844 Generator loss: 0.6001 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.4761 Generator loss: 0.6771 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.5973 Generator loss: 0.6548 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.3979 Generator loss: 0.8049 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.5500 Generator loss: 0.7721 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.4877 Generator loss: 0.6667
Batches: 6%|████▌ | 400/6331 [00:53<13:19, 7.42batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.5855 Generator loss: 0.5881 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.3911 Generator loss: 0.7343 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.5023 Generator loss: 0.5793 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.4787 Generator loss: 0.7153 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.4467 Generator loss: 0.7697 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.4534 Generator loss: 0.6112 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.3819 Generator loss: 0.8482 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.5866 Generator loss: 0.6314 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.7906 Generator loss: 0.5196 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.4754 Generator loss: 0.7509
Batches: 8%|█████▊ | 500/6331 [01:06<13:03, 7.44batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.4442 Generator loss: 0.7179 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.5375 Generator loss: 0.6713 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.3722 Generator loss: 0.8783 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.5356 Generator loss: 0.7056 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.5583 Generator loss: 0.6964 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.4328 Generator loss: 0.8849 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.3792 Generator loss: 0.8276 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.5893 Generator loss: 0.6000 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.3656 Generator loss: 0.7745 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.4371 Generator loss: 0.7874
Batches: 9%|██████▉ | 600/6331 [01:19<12:39, 7.54batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.3963 Generator loss: 0.8388 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.4776 Generator loss: 0.6906 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.5750 Generator loss: 0.6893 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.6879 Generator loss: 0.5897 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.6047 Generator loss: 0.6336 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.4282 Generator loss: 0.7359 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.4223 Generator loss: 0.7257 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.7057 Generator loss: 0.5891 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.4539 Generator loss: 0.7572 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.4163 Generator loss: 0.7341
Batches: 11%|████████ | 700/6331 [01:32<12:26, 7.54batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.6688 Generator loss: 0.5535 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.5756 Generator loss: 0.6039 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.4879 Generator loss: 0.6845 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.4919 Generator loss: 0.7714 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.4611 Generator loss: 0.7287 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.4178 Generator loss: 0.7238 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.4329 Generator loss: 0.9121 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.5194 Generator loss: 0.7347 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.4582 Generator loss: 0.7056 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.4564 Generator loss: 0.8823
Batches: 13%|█████████▏ | 800/6331 [01:45<12:09, 7.58batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.5464 Generator loss: 0.7426 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.5021 Generator loss: 0.6441 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.4522 Generator loss: 0.8113 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.4380 Generator loss: 0.8660 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.4066 Generator loss: 0.8001 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.4052 Generator loss: 0.7386 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.4357 Generator loss: 0.7732 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.4494 Generator loss: 0.7014 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.4250 Generator loss: 0.7745 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.5385 Generator loss: 0.6152
Batches: 14%|██████████▍ | 900/6331 [01:59<12:04, 7.50batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.4565 Generator loss: 0.7123 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.6896 Generator loss: 0.6131 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.5622 Generator loss: 0.8012 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.4494 Generator loss: 0.7379 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.4742 Generator loss: 0.6700 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.5877 Generator loss: 0.6041 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.3682 Generator loss: 0.7343 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.5526 Generator loss: 0.6682 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.5086 Generator loss: 0.7364 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.4250 Generator loss: 0.7659
Batches: 16%|███████████▎ | 1000/6331 [02:13<11:57, 7.43batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.4057 Generator loss: 0.7200 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.5781 Generator loss: 0.6293 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.5758 Generator loss: 0.6869 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.4938 Generator loss: 0.8690 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.4802 Generator loss: 0.6954 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.4697 Generator loss: 0.7706 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.6432 Generator loss: 0.7172 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.4216 Generator loss: 0.7061 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.5250 Generator loss: 0.8408 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.4915 Generator loss: 0.7298
Batches: 17%|████████████▌ | 1100/6331 [02:26<11:42, 7.44batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.4663 Generator loss: 0.7500 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.4500 Generator loss: 0.6810 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.5270 Generator loss: 0.7236 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.5270 Generator loss: 0.7142 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.4693 Generator loss: 0.8434 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.4611 Generator loss: 0.7162 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.4752 Generator loss: 0.6593 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.3863 Generator loss: 0.7861 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.4613 Generator loss: 0.7268 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.4548 Generator loss: 0.6965
Batches: 19%|█████████████▋ | 1200/6331 [02:39<11:22, 7.52batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.6500 Generator loss: 0.6799 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.5171 Generator loss: 0.7151 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.5061 Generator loss: 0.6941 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.3931 Generator loss: 0.7958 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.3935 Generator loss: 0.7035 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.5166 Generator loss: 0.6979 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.4087 Generator loss: 0.8217 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.4132 Generator loss: 0.7570 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.4666 Generator loss: 0.8890 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.4299 Generator loss: 0.8287
Batches: 21%|██████████████▊ | 1300/6331 [02:53<11:13, 7.47batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.4734 Generator loss: 0.9337 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.4099 Generator loss: 0.7270 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.4497 Generator loss: 0.6995 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.4564 Generator loss: 0.9141 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.4805 Generator loss: 0.6930 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.4633 Generator loss: 0.9194 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.4208 Generator loss: 0.8210 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.4505 Generator loss: 0.7011 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.4692 Generator loss: 0.7158 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.4627 Generator loss: 0.7779
Batches: 22%|███████████████▉ | 1400/6331 [03:06<10:53, 7.54batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.3741 Generator loss: 0.7109 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.5362 Generator loss: 0.8485 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.4457 Generator loss: 0.6579 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.3899 Generator loss: 0.7696 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4902 Generator loss: 0.7148 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.4713 Generator loss: 0.6902 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.4205 Generator loss: 0.7676 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.5338 Generator loss: 0.7645 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4346 Generator loss: 0.7409 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.4618 Generator loss: 0.6127
Batches: 24%|█████████████████ | 1500/6331 [03:19<10:36, 7.59batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.3967 Generator loss: 0.7957 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.5395 Generator loss: 0.6828 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.4129 Generator loss: 0.6988 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.3720 Generator loss: 0.8463 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.4807 Generator loss: 0.6425 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.4654 Generator loss: 0.9003 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.5243 Generator loss: 0.8602 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.4837 Generator loss: 0.7593 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.4907 Generator loss: 0.7162 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.4019 Generator loss: 0.7055
Batches: 25%|██████████████████▏ | 1600/6331 [03:32<10:25, 7.56batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.4224 Generator loss: 0.7653 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.4671 Generator loss: 0.6306 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.4562 Generator loss: 0.7693 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.4141 Generator loss: 0.7854 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.3936 Generator loss: 0.8050 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.4221 Generator loss: 0.7116 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4668 Generator loss: 0.8432 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.4917 Generator loss: 0.7386 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.4626 Generator loss: 0.7083 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.5095 Generator loss: 0.7069
Batches: 27%|███████████████████▎ | 1700/6331 [03:45<10:08, 7.61batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.5452 Generator loss: 0.8078 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.4723 Generator loss: 0.6561 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.4595 Generator loss: 0.7194 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.4588 Generator loss: 0.7698 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.4771 Generator loss: 0.7332 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.4416 Generator loss: 0.7482 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4048 Generator loss: 0.7348 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.4722 Generator loss: 0.8244 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.3750 Generator loss: 0.7759 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.5276 Generator loss: 0.6933
Batches: 28%|████████████████████▍ | 1800/6331 [03:59<10:05, 7.49batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.3803 Generator loss: 0.7585 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.5522 Generator loss: 0.7614 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.4242 Generator loss: 0.8624 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.4757 Generator loss: 0.8650 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.4556 Generator loss: 0.6756 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.3800 Generator loss: 0.8727 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.5064 Generator loss: 0.6919 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.4950 Generator loss: 0.9214 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.3938 Generator loss: 0.6086 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4366 Generator loss: 0.9102
Batches: 30%|█████████████████████▌ | 1900/6331 [04:13<09:57, 7.42batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.3894 Generator loss: 0.7803 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.4207 Generator loss: 0.7322 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.4195 Generator loss: 0.8220 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.4096 Generator loss: 0.7647 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.4178 Generator loss: 0.6735 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.4469 Generator loss: 0.7420 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.3857 Generator loss: 0.8006 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.4470 Generator loss: 0.7346 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.4971 Generator loss: 0.6824 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.3736 Generator loss: 0.9576
Batches: 32%|██████████████████████▋ | 2000/6331 [04:26<09:38, 7.49batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.6421 Generator loss: 0.9141 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.3849 Generator loss: 0.7169 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.7270 Generator loss: 0.5534 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.5363 Generator loss: 0.6758 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.5750 Generator loss: 0.6863 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4619 Generator loss: 0.6848 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.4519 Generator loss: 0.7873 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.3664 Generator loss: 0.7842 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.4442 Generator loss: 0.7046 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.4530 Generator loss: 0.6895
Batches: 33%|███████████████████████▉ | 2100/6331 [04:39<09:20, 7.55batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.4366 Generator loss: 0.7398 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.4968 Generator loss: 0.7002 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.4693 Generator loss: 0.6822 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.4399 Generator loss: 0.8022 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4958 Generator loss: 0.7280 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.6438 Generator loss: 0.6171 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.5010 Generator loss: 0.6422 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.4149 Generator loss: 0.7618 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.4895 Generator loss: 0.8096 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.6069 Generator loss: 0.6965
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Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.5250 Generator loss: 0.7374 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.4601 Generator loss: 0.8752 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.4466 Generator loss: 0.7694 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.4335 Generator loss: 0.7932 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.4743 Generator loss: 0.6656 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.4735 Generator loss: 0.7128 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.4118 Generator loss: 0.8387 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4042 Generator loss: 0.8382 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.4215 Generator loss: 0.9659 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.4443 Generator loss: 0.7332
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Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.3996 Generator loss: 0.7925 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.4031 Generator loss: 0.8124 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.4525 Generator loss: 0.8020 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.4672 Generator loss: 0.8387 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.5039 Generator loss: 0.6340 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.4189 Generator loss: 0.7115 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.4969 Generator loss: 0.7563 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.4103 Generator loss: 0.8050 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4276 Generator loss: 0.7953 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.4052 Generator loss: 0.6531
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Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.4533 Generator loss: 0.6925 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.4441 Generator loss: 0.7309 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.4718 Generator loss: 0.6618 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.5477 Generator loss: 0.7271 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.5828 Generator loss: 0.6753 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.4171 Generator loss: 0.8025 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.3623 Generator loss: 0.7950 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.5303 Generator loss: 0.7280 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.4558 Generator loss: 0.8475 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.3863 Generator loss: 0.8101
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Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.3559 Generator loss: 0.7804 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.4539 Generator loss: 0.8487 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.3684 Generator loss: 0.7332 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.5070 Generator loss: 0.9711 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.4011 Generator loss: 0.7775 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.4172 Generator loss: 0.8747 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.3839 Generator loss: 0.8535 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.4294 Generator loss: 0.7492 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.4897 Generator loss: 0.8284 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.4509 Generator loss: 0.7921
Batches: 41%|█████████████████████████████▌ | 2600/6331 [05:45<08:12, 7.57batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.4260 Generator loss: 0.8232 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.4455 Generator loss: 0.7458 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.4200 Generator loss: 0.8538 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.4257 Generator loss: 0.7129 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.4554 Generator loss: 0.6731 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.4396 Generator loss: 0.7635 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.4524 Generator loss: 0.7266 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.4519 Generator loss: 0.6753 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.4016 Generator loss: 0.7819 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.4003 Generator loss: 0.6796
Batches: 43%|██████████████████████████████▋ | 2700/6331 [05:58<08:01, 7.55batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.4050 Generator loss: 0.8418 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.5463 Generator loss: 0.8748 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.3854 Generator loss: 0.7089 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.4001 Generator loss: 0.7008 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.4144 Generator loss: 0.8850 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.3826 Generator loss: 0.8380 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.4218 Generator loss: 0.6961 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.4330 Generator loss: 0.7597 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.4919 Generator loss: 0.7167 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.4727 Generator loss: 0.7995
Batches: 44%|███████████████████████████████▊ | 2800/6331 [06:13<08:00, 7.35batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.3977 Generator loss: 1.0860 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.4400 Generator loss: 0.8409 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.4081 Generator loss: 0.8277 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.4280 Generator loss: 0.6578 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.4467 Generator loss: 0.7151 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.3866 Generator loss: 0.7981 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.4326 Generator loss: 0.9324 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4338 Generator loss: 0.7995 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.3918 Generator loss: 0.8557 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.4125 Generator loss: 0.6762
Batches: 46%|████████████████████████████████▉ | 2900/6331 [06:26<07:40, 7.45batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4087 Generator loss: 0.7639 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4446 Generator loss: 0.7396 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.4151 Generator loss: 0.8342 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.3998 Generator loss: 0.7693 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.4129 Generator loss: 0.8045 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.3533 Generator loss: 0.9188 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.3891 Generator loss: 0.7554 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.4178 Generator loss: 0.8110 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.3758 Generator loss: 0.7598 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.4385 Generator loss: 0.7598
Batches: 47%|██████████████████████████████████ | 3000/6331 [06:39<07:26, 7.46batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.3989 Generator loss: 0.6626 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.4749 Generator loss: 0.7801 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.4829 Generator loss: 0.7039 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.4887 Generator loss: 0.6227 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.4368 Generator loss: 0.5875 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.4447 Generator loss: 0.8082 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.3994 Generator loss: 0.8358 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.3696 Generator loss: 0.8064 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.5305 Generator loss: 0.7110 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.4378 Generator loss: 0.7415
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [06:52<07:12, 7.48batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.3909 Generator loss: 0.8071 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.4056 Generator loss: 0.7974 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4649 Generator loss: 0.7629 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.4069 Generator loss: 0.7518 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.4053 Generator loss: 0.7212 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.3959 Generator loss: 0.7104 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.4197 Generator loss: 0.7198 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.4459 Generator loss: 0.6906 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.4503 Generator loss: 0.8344 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4201 Generator loss: 0.7120
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [07:06<06:58, 7.48batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4052 Generator loss: 0.6506 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4177 Generator loss: 0.8529 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.4172 Generator loss: 0.8143 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.4429 Generator loss: 0.7187 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.4062 Generator loss: 0.6184 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.4389 Generator loss: 0.7684 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.3996 Generator loss: 0.7745 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.4100 Generator loss: 0.7447 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.4194 Generator loss: 0.7953 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.4413 Generator loss: 0.7971
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [07:19<06:41, 7.55batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.3817 Generator loss: 0.8237 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.4003 Generator loss: 0.9521 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.4365 Generator loss: 0.8864 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.4137 Generator loss: 0.8571 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4079 Generator loss: 0.7901 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.3690 Generator loss: 0.7999 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.4088 Generator loss: 0.8132 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.3987 Generator loss: 0.7089 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.3895 Generator loss: 0.8340 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.3884 Generator loss: 0.7832
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [07:32<06:28, 7.54batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.4001 Generator loss: 0.8122 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.4252 Generator loss: 0.7606 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.4198 Generator loss: 0.7285 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.4183 Generator loss: 0.8513 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3860 Generator loss: 0.7713 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.4678 Generator loss: 0.7799 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.4359 Generator loss: 0.6066 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.4338 Generator loss: 0.6290 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.4685 Generator loss: 0.6776 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.4212 Generator loss: 0.8688
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [07:45<06:13, 7.58batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.3955 Generator loss: 0.7720 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.4045 Generator loss: 0.7508 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.4065 Generator loss: 0.7683 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.3846 Generator loss: 0.8602 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.4087 Generator loss: 0.8805 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.3713 Generator loss: 0.8408 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.4146 Generator loss: 0.9615 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.4019 Generator loss: 0.7776 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.4277 Generator loss: 0.7843 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.4249 Generator loss: 0.6886
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [07:58<06:01, 7.56batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.4017 Generator loss: 0.8236 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.3897 Generator loss: 0.8635 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.3910 Generator loss: 0.7671 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.4090 Generator loss: 0.7752 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.3985 Generator loss: 0.8391 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.4346 Generator loss: 0.6125 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3785 Generator loss: 0.7349 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.3914 Generator loss: 0.6820 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.4614 Generator loss: 0.8386 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.4443 Generator loss: 0.7012
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [08:12<05:51, 7.49batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.3764 Generator loss: 0.9372 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.4001 Generator loss: 0.8204 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.3904 Generator loss: 0.7974 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.3906 Generator loss: 0.8100 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.3885 Generator loss: 0.7605 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.3997 Generator loss: 0.7923 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.3997 Generator loss: 0.8404 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.3904 Generator loss: 0.8567 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.3830 Generator loss: 0.8050 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.3881 Generator loss: 0.8612
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [08:25<05:38, 7.48batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.3758 Generator loss: 0.8845 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.3956 Generator loss: 0.8072 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.3952 Generator loss: 0.8386 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.4068 Generator loss: 0.9173 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.4345 Generator loss: 0.6976 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.4273 Generator loss: 0.8186 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.3955 Generator loss: 0.7535 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.4133 Generator loss: 0.6966 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.4031 Generator loss: 0.8027 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.4101 Generator loss: 0.7364
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [08:38<05:22, 7.53batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.3874 Generator loss: 0.8105 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.4056 Generator loss: 0.6611 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.4259 Generator loss: 0.6759 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.4205 Generator loss: 0.8334 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.3883 Generator loss: 0.7715 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.4117 Generator loss: 0.6757 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.3825 Generator loss: 0.8337 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.3864 Generator loss: 0.7757 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.4187 Generator loss: 0.7373 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.3880 Generator loss: 0.7355
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [08:52<05:11, 7.48batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.3713 Generator loss: 0.7595 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.3866 Generator loss: 0.8183 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.3870 Generator loss: 0.8282 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.4340 Generator loss: 0.9868 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.3688 Generator loss: 0.7974 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.3988 Generator loss: 0.7908 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.4090 Generator loss: 0.7674 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.3681 Generator loss: 0.8951 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.3785 Generator loss: 0.7726 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.3993 Generator loss: 0.7343
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [09:05<04:58, 7.47batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.4044 Generator loss: 0.8303 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.3981 Generator loss: 0.7475 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.4118 Generator loss: 0.7550 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.4052 Generator loss: 0.7617 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.4101 Generator loss: 0.7312 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.4283 Generator loss: 0.6928 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.4040 Generator loss: 0.8240 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.4064 Generator loss: 0.7540 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.4211 Generator loss: 0.7299 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.4175 Generator loss: 0.8027
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.4016 Generator loss: 0.7747 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.4124 Generator loss: 0.7214 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.4074 Generator loss: 0.8236 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.3970 Generator loss: 0.7421 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.4062 Generator loss: 0.7851 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.3990 Generator loss: 0.7096 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.3934 Generator loss: 0.8200 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.4090 Generator loss: 0.6383 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.4052 Generator loss: 0.7632 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.3972 Generator loss: 0.7477
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.4159 Generator loss: 0.8356 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.4162 Generator loss: 0.6699 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3608 Generator loss: 0.7175 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.3938 Generator loss: 0.7537 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.3772 Generator loss: 0.6936 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.3820 Generator loss: 0.7782 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.3957 Generator loss: 0.7225 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.4076 Generator loss: 0.7670 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.3872 Generator loss: 0.7143 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.3837 Generator loss: 0.8113
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Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.3824 Generator loss: 0.7395 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.4107 Generator loss: 0.7948 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.4115 Generator loss: 0.7630 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.3977 Generator loss: 0.7693 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.3970 Generator loss: 0.7741 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.3941 Generator loss: 0.7287 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.4045 Generator loss: 0.7358 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.4255 Generator loss: 0.7657 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.3841 Generator loss: 0.8584 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.4063 Generator loss: 0.7658
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Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.3796 Generator loss: 0.7969 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.3842 Generator loss: 0.8482 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.3905 Generator loss: 0.7565 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.3951 Generator loss: 0.7300 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.3903 Generator loss: 0.7797 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.3981 Generator loss: 0.7365 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.3912 Generator loss: 0.7544 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.3774 Generator loss: 0.7894 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.3712 Generator loss: 0.7674 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.4107 Generator loss: 0.8293
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Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.3738 Generator loss: 0.8156 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3776 Generator loss: 0.7668 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3825 Generator loss: 0.7690 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.4166 Generator loss: 0.7295 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.4279 Generator loss: 0.8127 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.4628 Generator loss: 0.7993 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.4027 Generator loss: 0.8158 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.4319 Generator loss: 0.6235 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.3880 Generator loss: 0.8493 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.3702 Generator loss: 0.7605
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [10:39<03:25, 7.45batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.3967 Generator loss: 0.8250 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.4246 Generator loss: 0.7008 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.3737 Generator loss: 0.7909 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.4107 Generator loss: 0.7473 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.3769 Generator loss: 0.8536 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.3894 Generator loss: 0.8147 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3887 Generator loss: 0.7109 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.3782 Generator loss: 0.7207 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.3676 Generator loss: 0.7919 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.4499 Generator loss: 0.8256
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [10:53<03:12, 7.42batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.4090 Generator loss: 0.7574 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.3739 Generator loss: 0.7717 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.4052 Generator loss: 0.7005 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.4093 Generator loss: 0.7268 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.4017 Generator loss: 0.8523 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.4030 Generator loss: 0.7650 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.4025 Generator loss: 0.7971 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.3765 Generator loss: 0.7502 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.3947 Generator loss: 0.7910 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.3888 Generator loss: 0.8891
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [11:06<02:59, 7.43batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.3688 Generator loss: 0.8371 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.4165 Generator loss: 0.8417 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.4058 Generator loss: 0.6577 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.3911 Generator loss: 0.7546 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.3884 Generator loss: 0.7153 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.4009 Generator loss: 0.7752 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.4263 Generator loss: 0.7465 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.3964 Generator loss: 0.7659 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.4100 Generator loss: 0.6830 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.4133 Generator loss: 0.7126
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [11:19<02:44, 7.50batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.4016 Generator loss: 0.8019 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.3940 Generator loss: 0.7250 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.4014 Generator loss: 0.8073 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.4195 Generator loss: 0.7793 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.4182 Generator loss: 0.6895 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3807 Generator loss: 0.8496 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.3916 Generator loss: 0.8213 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.3857 Generator loss: 0.8174 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.3883 Generator loss: 0.7896 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.3855 Generator loss: 0.8541
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [11:33<02:30, 7.52batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.3972 Generator loss: 0.7688 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.3939 Generator loss: 0.8196 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.3946 Generator loss: 0.7990 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.3754 Generator loss: 0.7801 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.4006 Generator loss: 0.7680 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.4065 Generator loss: 0.7546 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.4079 Generator loss: 0.7247 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.4085 Generator loss: 0.7135 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.4043 Generator loss: 0.8029 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.3787 Generator loss: 0.7310
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [11:46<02:17, 7.47batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.4285 Generator loss: 0.7945 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3819 Generator loss: 0.8208 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3836 Generator loss: 0.7765 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.4039 Generator loss: 0.8783 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.3790 Generator loss: 0.7427 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.4127 Generator loss: 0.7069 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3731 Generator loss: 0.7691 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.4039 Generator loss: 0.7546 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3803 Generator loss: 0.8524 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.4041 Generator loss: 0.8285
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [12:00<02:05, 7.42batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3730 Generator loss: 0.8586 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3844 Generator loss: 0.8115 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3804 Generator loss: 0.7701 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3850 Generator loss: 0.8631 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.4134 Generator loss: 0.6296 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3765 Generator loss: 0.7805 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3991 Generator loss: 0.8216 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.3952 Generator loss: 0.7243 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.4068 Generator loss: 0.7640 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.3877 Generator loss: 0.8562
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Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.3914 Generator loss: 0.8002 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3739 Generator loss: 0.8077 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3952 Generator loss: 0.8064 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.4247 Generator loss: 0.7211 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3776 Generator loss: 0.7898 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.4022 Generator loss: 0.8059 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3873 Generator loss: 0.8235 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.3940 Generator loss: 0.7890 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.3865 Generator loss: 0.7704 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.3891 Generator loss: 0.7736
Batches: 88%|███████████████████████████████████████████████████████████████▋ | 5600/6331 [12:27<01:38, 7.40batch/s]
Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.3962 Generator loss: 0.7828 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3890 Generator loss: 0.7613 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3897 Generator loss: 0.8094 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3772 Generator loss: 0.7676 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.3961 Generator loss: 0.7038 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3795 Generator loss: 0.7385 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3756 Generator loss: 0.8224 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.3813 Generator loss: 0.7487 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.3898 Generator loss: 0.8703 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3812 Generator loss: 0.7811
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Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3934 Generator loss: 0.7379 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.3931 Generator loss: 0.7408 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.3962 Generator loss: 0.8046 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.4282 Generator loss: 0.7192 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.3991 Generator loss: 0.7553 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.4130 Generator loss: 0.7888 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.4101 Generator loss: 0.6632 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.3870 Generator loss: 0.8241 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3729 Generator loss: 0.8563 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.3972 Generator loss: 0.7449
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Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.4020 Generator loss: 0.7157 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.3938 Generator loss: 0.8823 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.4000 Generator loss: 0.6647 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.3801 Generator loss: 0.8558 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.4068 Generator loss: 0.7224 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.3843 Generator loss: 0.7700 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3920 Generator loss: 0.7448 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.3885 Generator loss: 0.7561 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.3810 Generator loss: 0.7540 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3774 Generator loss: 0.8259
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3959 Generator loss: 0.8120 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3976 Generator loss: 0.7772 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3966 Generator loss: 0.8268 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3863 Generator loss: 0.7852 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.4138 Generator loss: 0.8445 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.3981 Generator loss: 0.8455 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3813 Generator loss: 0.8000 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.3945 Generator loss: 0.7415 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.4105 Generator loss: 0.8730 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3919 Generator loss: 0.8035
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.3736 Generator loss: 0.8933 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3861 Generator loss: 0.8320 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3947 Generator loss: 0.7531 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.4050 Generator loss: 0.7460 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3982 Generator loss: 0.7382 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.3949 Generator loss: 0.6936 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.3796 Generator loss: 0.8090 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.3804 Generator loss: 0.7835 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.3804 Generator loss: 0.7849 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3951 Generator loss: 0.8271
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.3821 Generator loss: 0.6950 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.4087 Generator loss: 0.7940 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3911 Generator loss: 0.8688 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.3829 Generator loss: 0.8291 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.4130 Generator loss: 0.6914 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.3835 Generator loss: 0.7598 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.3946 Generator loss: 0.7188 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.4002 Generator loss: 0.8288 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3949 Generator loss: 0.7998 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3742 Generator loss: 0.8707
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [13:47<00:17, 7.49batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.4047 Generator loss: 0.7668 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3992 Generator loss: 0.7782 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3913 Generator loss: 0.8209 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3912 Generator loss: 0.8132 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.3893 Generator loss: 0.7982 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3881 Generator loss: 0.7692 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3867 Generator loss: 0.7545 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3848 Generator loss: 0.7290 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3814 Generator loss: 0.7539 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3867 Generator loss: 0.8238
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [14:00<00:04, 7.46batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.3691 Generator loss: 0.7961 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.3828 Generator loss: 0.7983 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3931 Generator loss: 0.7610
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [14:05<00:00, 845.02s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.001
beta1 = 0.3 # the losses seem to vary less, but the visuals are still bad
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 10.4056 Generator loss: 0.0001 Epoch 0/1... Batch 20/6331... Discriminator loss: 4.0650 Generator loss: 0.0846 Epoch 0/1... Batch 30/6331... Discriminator loss: 2.5723 Generator loss: 0.1731 Epoch 0/1... Batch 40/6331... Discriminator loss: 1.8835 Generator loss: 0.3129 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.8609 Generator loss: 0.5904 Epoch 0/1... Batch 60/6331... Discriminator loss: 2.0750 Generator loss: 1.4860 Epoch 0/1... Batch 70/6331... Discriminator loss: 2.3003 Generator loss: 0.2562 Epoch 0/1... Batch 80/6331... Discriminator loss: 1.8901 Generator loss: 0.4367 Epoch 0/1... Batch 90/6331... Discriminator loss: 1.8324 Generator loss: 0.6193 Epoch 0/1... Batch 100/6331... Discriminator loss: 1.6307 Generator loss: 0.6006
Batches: 2%|█▏ | 100/6331 [00:13<14:11, 7.32batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 1.4872 Generator loss: 0.9883 Epoch 0/1... Batch 120/6331... Discriminator loss: 1.6589 Generator loss: 0.6321 Epoch 0/1... Batch 130/6331... Discriminator loss: 1.6368 Generator loss: 0.6155 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.6559 Generator loss: 0.5191 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.6236 Generator loss: 0.6155 Epoch 0/1... Batch 160/6331... Discriminator loss: 1.5269 Generator loss: 0.6294 Epoch 0/1... Batch 170/6331... Discriminator loss: 1.8081 Generator loss: 0.5218 Epoch 0/1... Batch 180/6331... Discriminator loss: 1.8372 Generator loss: 0.4246 Epoch 0/1... Batch 190/6331... Discriminator loss: 1.5381 Generator loss: 0.7126 Epoch 0/1... Batch 200/6331... Discriminator loss: 1.5079 Generator loss: 0.6517
Batches: 3%|██▎ | 200/6331 [00:27<13:59, 7.31batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.5709 Generator loss: 0.6491 Epoch 0/1... Batch 220/6331... Discriminator loss: 1.5871 Generator loss: 0.7032 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.4959 Generator loss: 0.7392 Epoch 0/1... Batch 240/6331... Discriminator loss: 1.5441 Generator loss: 0.5996 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.6637 Generator loss: 0.5064 Epoch 0/1... Batch 260/6331... Discriminator loss: 1.5341 Generator loss: 0.6727 Epoch 0/1... Batch 270/6331... Discriminator loss: 1.5182 Generator loss: 0.8540 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.4799 Generator loss: 0.7007 Epoch 0/1... Batch 290/6331... Discriminator loss: 1.4984 Generator loss: 0.8754 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.3619 Generator loss: 0.7930
Batches: 5%|███▍ | 300/6331 [00:41<13:48, 7.28batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.5283 Generator loss: 0.6061 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.4871 Generator loss: 0.6821 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.4720 Generator loss: 0.7444 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.4548 Generator loss: 0.7370 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.4864 Generator loss: 0.6868 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.5173 Generator loss: 0.6263 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.5234 Generator loss: 0.6188 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.5922 Generator loss: 0.5785 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.4578 Generator loss: 0.7792 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.5291 Generator loss: 0.7264
Batches: 6%|████▌ | 400/6331 [00:57<14:13, 6.95batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.5917 Generator loss: 0.6207 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.5245 Generator loss: 0.7219 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.5410 Generator loss: 0.5125 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.7262 Generator loss: 0.5531 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.4264 Generator loss: 0.7698 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.5525 Generator loss: 0.5575 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.5002 Generator loss: 0.6173 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.5452 Generator loss: 0.8027 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.5993 Generator loss: 0.6056 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.5972 Generator loss: 0.7396
Batches: 8%|█████▊ | 500/6331 [01:10<13:44, 7.07batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.4630 Generator loss: 0.7994 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.4712 Generator loss: 0.6652 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.4872 Generator loss: 0.5864 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.5692 Generator loss: 0.5892 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.4814 Generator loss: 0.8169 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.5252 Generator loss: 0.5870 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.4432 Generator loss: 0.7207 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.4296 Generator loss: 0.7426 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.4324 Generator loss: 0.7715 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.5296 Generator loss: 0.8390
Batches: 9%|██████▉ | 600/6331 [01:24<13:20, 7.15batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.4992 Generator loss: 0.7192 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.5412 Generator loss: 0.6327 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.5492 Generator loss: 0.7863 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.5144 Generator loss: 0.8777 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.4731 Generator loss: 0.9081 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.4062 Generator loss: 0.7661 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.4843 Generator loss: 0.7719 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.5631 Generator loss: 0.5578 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.5180 Generator loss: 1.0067 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.5453 Generator loss: 0.7020
Batches: 11%|████████ | 700/6331 [01:38<13:06, 7.16batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.5132 Generator loss: 0.6286 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.5227 Generator loss: 0.7711 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.5330 Generator loss: 0.5742 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.6402 Generator loss: 0.5182 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.4671 Generator loss: 0.9460 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.4148 Generator loss: 0.7147 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.5048 Generator loss: 0.8152 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.4666 Generator loss: 0.6524 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.5634 Generator loss: 0.5980 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.5071 Generator loss: 0.6656
Batches: 13%|█████████▏ | 800/6331 [01:51<12:45, 7.23batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.4503 Generator loss: 0.7036 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.4744 Generator loss: 0.6592 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.4376 Generator loss: 0.7384 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.4758 Generator loss: 0.7952 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.5332 Generator loss: 0.6907 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.4548 Generator loss: 0.7618 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.4409 Generator loss: 0.5808 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.4599 Generator loss: 0.7021 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.5206 Generator loss: 0.9070 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.5088 Generator loss: 0.7213
Batches: 14%|██████████▍ | 900/6331 [02:06<12:38, 7.16batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.4826 Generator loss: 0.8321 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.4348 Generator loss: 0.7238 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.5093 Generator loss: 0.5972 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.4724 Generator loss: 0.8674 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.6190 Generator loss: 0.6238 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.5462 Generator loss: 0.6250 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.4397 Generator loss: 0.6141 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.4547 Generator loss: 0.7054 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.5129 Generator loss: 0.5681 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.7008 Generator loss: 0.5409
Batches: 16%|███████████▎ | 1000/6331 [02:20<12:30, 7.11batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.5509 Generator loss: 0.5441 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.4225 Generator loss: 0.8024 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.4724 Generator loss: 0.7372 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.4208 Generator loss: 0.7847 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.4231 Generator loss: 0.8531 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.4328 Generator loss: 0.9685 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.4399 Generator loss: 0.8271 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.4731 Generator loss: 0.6983 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.3947 Generator loss: 0.6943 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.4738 Generator loss: 0.5916
Batches: 17%|████████████▌ | 1100/6331 [02:34<12:16, 7.10batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.6057 Generator loss: 1.2012 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.5004 Generator loss: 0.9172 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.4520 Generator loss: 0.8493 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.5927 Generator loss: 0.9152 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.4148 Generator loss: 0.7432 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.3848 Generator loss: 0.7263 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.5048 Generator loss: 0.7542 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.4680 Generator loss: 0.8510 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.5222 Generator loss: 0.6151 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.4514 Generator loss: 0.6726
Batches: 19%|█████████████▋ | 1200/6331 [02:48<11:57, 7.15batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.6031 Generator loss: 0.6141 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.3806 Generator loss: 0.8728 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.4598 Generator loss: 0.8108 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.4359 Generator loss: 0.7651 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.4061 Generator loss: 0.7846 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.4528 Generator loss: 0.6714 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.4308 Generator loss: 0.8223 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.4720 Generator loss: 0.8711 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.4423 Generator loss: 0.7576 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.4429 Generator loss: 0.7720
Batches: 21%|██████████████▊ | 1300/6331 [03:02<11:52, 7.06batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.3938 Generator loss: 0.7813 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.3964 Generator loss: 0.7614 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.4033 Generator loss: 0.8593 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.4577 Generator loss: 0.7541 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.4566 Generator loss: 0.6341 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.4696 Generator loss: 0.9610 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.4018 Generator loss: 0.8148 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.3748 Generator loss: 0.8001 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.5421 Generator loss: 0.6139 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.4715 Generator loss: 0.9179
Batches: 22%|███████████████▉ | 1400/6331 [03:16<11:30, 7.14batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.4336 Generator loss: 0.7580 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.4289 Generator loss: 0.7811 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.4412 Generator loss: 0.6539 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.4338 Generator loss: 1.0129 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4449 Generator loss: 0.7352 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.4104 Generator loss: 0.8365 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.4471 Generator loss: 0.6600 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.3774 Generator loss: 0.9315 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4521 Generator loss: 0.5746 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.5247 Generator loss: 0.8298
Batches: 24%|█████████████████ | 1500/6331 [03:30<11:15, 7.15batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.4844 Generator loss: 0.8657 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.5331 Generator loss: 0.5291 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.5163 Generator loss: 0.7155 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.4453 Generator loss: 0.6720 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.4509 Generator loss: 0.6940 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.4101 Generator loss: 0.7391 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.3894 Generator loss: 0.7888 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.4223 Generator loss: 0.6921 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.4233 Generator loss: 0.9760 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.3769 Generator loss: 0.7703
Batches: 25%|██████████████████▏ | 1600/6331 [03:43<10:52, 7.25batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.5204 Generator loss: 0.4922 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.4654 Generator loss: 0.6509 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.6136 Generator loss: 0.7728 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.4345 Generator loss: 0.7324 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.4994 Generator loss: 0.7754 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.4876 Generator loss: 0.8990 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4251 Generator loss: 0.9123 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.4389 Generator loss: 0.6545 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.4413 Generator loss: 0.7340 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.4269 Generator loss: 0.6930
Batches: 27%|███████████████████▎ | 1700/6331 [03:56<10:29, 7.36batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.4803 Generator loss: 0.6196 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.4337 Generator loss: 0.7596 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.4398 Generator loss: 0.8944 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.4668 Generator loss: 0.7429 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.4926 Generator loss: 0.6552 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.4513 Generator loss: 0.8435 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4093 Generator loss: 0.7479 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.4843 Generator loss: 0.8824 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.4963 Generator loss: 0.5365 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.3869 Generator loss: 0.8014
Batches: 28%|████████████████████▍ | 1800/6331 [04:10<10:09, 7.43batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.3717 Generator loss: 0.7453 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.4468 Generator loss: 0.6663 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.3601 Generator loss: 0.8876 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.4345 Generator loss: 0.8050 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.4225 Generator loss: 0.6850 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.3976 Generator loss: 0.9205 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.3933 Generator loss: 0.7796 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.4214 Generator loss: 0.6830 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.4232 Generator loss: 0.5729 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4439 Generator loss: 0.7735
Batches: 30%|█████████████████████▌ | 1900/6331 [04:23<09:57, 7.41batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.5473 Generator loss: 0.8159 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.4155 Generator loss: 0.7710 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.4283 Generator loss: 0.7639 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.5175 Generator loss: 0.6875 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.4439 Generator loss: 0.6998 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.4280 Generator loss: 0.8901 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.4665 Generator loss: 0.8365 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.4017 Generator loss: 0.6999 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.4467 Generator loss: 0.6282 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.4757 Generator loss: 0.5988
Batches: 32%|██████████████████████▋ | 2000/6331 [04:37<09:49, 7.35batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.4311 Generator loss: 0.6676 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.4312 Generator loss: 0.7898 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.4328 Generator loss: 0.7322 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.4414 Generator loss: 0.7429 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.4060 Generator loss: 0.7998 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4187 Generator loss: 0.6819 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.5168 Generator loss: 0.6084 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.4213 Generator loss: 0.6485 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.4691 Generator loss: 0.5898 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.4049 Generator loss: 0.7160
Batches: 33%|███████████████████████▉ | 2100/6331 [04:51<09:40, 7.29batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.4367 Generator loss: 0.6885 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.4669 Generator loss: 0.6744 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.4601 Generator loss: 0.6640 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.4295 Generator loss: 0.8461 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4259 Generator loss: 0.8425 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.4715 Generator loss: 0.6946 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.4357 Generator loss: 0.8401 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.4142 Generator loss: 0.6569 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.3681 Generator loss: 0.7382 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.4187 Generator loss: 0.7227
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Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.4386 Generator loss: 0.8512 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.4268 Generator loss: 0.7682 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.4681 Generator loss: 0.6162 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.4736 Generator loss: 0.6977 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.4110 Generator loss: 0.6797 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.4607 Generator loss: 0.6504 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.4311 Generator loss: 0.8361 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4457 Generator loss: 0.6876 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.4550 Generator loss: 0.7372 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.4453 Generator loss: 0.8673
Batches: 36%|██████████████████████████▏ | 2300/6331 [05:20<09:25, 7.13batch/s]
Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.3991 Generator loss: 0.7876 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.4252 Generator loss: 0.6526 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.4429 Generator loss: 1.0704 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.4275 Generator loss: 0.8147 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.4672 Generator loss: 0.5719 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.4645 Generator loss: 0.7007 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.4307 Generator loss: 0.6808 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.4424 Generator loss: 0.7668 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4298 Generator loss: 0.6960 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.4074 Generator loss: 0.7557
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Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.3865 Generator loss: 0.8841 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.4098 Generator loss: 0.7615 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.4497 Generator loss: 0.8348 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.4470 Generator loss: 0.6510 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.4245 Generator loss: 0.7719 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.4741 Generator loss: 0.6822 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.3929 Generator loss: 0.7154 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.4218 Generator loss: 0.9171 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.3773 Generator loss: 0.7395 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.4279 Generator loss: 0.9215
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Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.4344 Generator loss: 0.7658 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.4317 Generator loss: 0.7120 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.3978 Generator loss: 0.7340 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.4977 Generator loss: 0.7423 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.4222 Generator loss: 0.7422 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.4280 Generator loss: 0.6572 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.4464 Generator loss: 0.8154 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.4795 Generator loss: 0.7361 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.4118 Generator loss: 0.7870 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.5921 Generator loss: 0.4878
Batches: 41%|█████████████████████████████▌ | 2600/6331 [06:02<08:44, 7.11batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.4128 Generator loss: 0.7531 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.4309 Generator loss: 0.8091 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.3679 Generator loss: 0.8329 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.4736 Generator loss: 0.9184 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.4299 Generator loss: 0.6667 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.4251 Generator loss: 0.6456 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.3915 Generator loss: 0.7298 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.3953 Generator loss: 0.6979 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.3911 Generator loss: 0.7765 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.4355 Generator loss: 0.7534
Batches: 43%|██████████████████████████████▋ | 2700/6331 [06:16<08:25, 7.19batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.3937 Generator loss: 0.7934 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.4091 Generator loss: 0.8337 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.4026 Generator loss: 0.7650 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.4355 Generator loss: 0.7522 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.4111 Generator loss: 0.8081 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.4083 Generator loss: 0.8062 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.4957 Generator loss: 0.6609 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.4223 Generator loss: 0.6795 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.4072 Generator loss: 0.8142 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.4619 Generator loss: 0.6769
Batches: 44%|███████████████████████████████▊ | 2800/6331 [06:30<08:11, 7.18batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.4331 Generator loss: 0.6889 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.4311 Generator loss: 0.8029 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.4052 Generator loss: 0.7512 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.4226 Generator loss: 0.6663 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.3922 Generator loss: 0.7377 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.3886 Generator loss: 0.7629 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.4981 Generator loss: 0.9296 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4204 Generator loss: 0.8574 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.4345 Generator loss: 0.9157 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.4093 Generator loss: 0.6824
Batches: 46%|████████████████████████████████▉ | 2900/6331 [06:43<07:51, 7.28batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4011 Generator loss: 0.7836 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4234 Generator loss: 0.7094 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.3965 Generator loss: 0.8032 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.4338 Generator loss: 0.8540 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.4719 Generator loss: 0.6555 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.4485 Generator loss: 0.7302 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.4077 Generator loss: 0.7647 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.3796 Generator loss: 0.7524 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.4468 Generator loss: 0.6430 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.3679 Generator loss: 0.7516
Batches: 47%|██████████████████████████████████ | 3000/6331 [06:58<07:47, 7.12batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.4012 Generator loss: 0.6853 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.4202 Generator loss: 0.7346 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.4450 Generator loss: 0.6406 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.4099 Generator loss: 0.8178 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.4648 Generator loss: 0.5787 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.4262 Generator loss: 0.7173 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.4136 Generator loss: 0.8694 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.3989 Generator loss: 0.7059 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.4287 Generator loss: 0.7222 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.3982 Generator loss: 0.7680
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [07:12<07:38, 7.05batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.4183 Generator loss: 0.6973 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.4142 Generator loss: 0.6575 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4187 Generator loss: 0.7426 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.3931 Generator loss: 0.7305 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.4112 Generator loss: 0.7588 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.4675 Generator loss: 0.6775 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.4172 Generator loss: 0.8081 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.4482 Generator loss: 0.6901 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.3991 Generator loss: 0.8035 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4122 Generator loss: 0.6341
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [07:27<07:30, 6.95batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4226 Generator loss: 0.7501 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4047 Generator loss: 0.8395 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.3994 Generator loss: 0.8342 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.3894 Generator loss: 0.7749 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.4031 Generator loss: 0.8467 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.3951 Generator loss: 0.8988 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.4095 Generator loss: 0.7050 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.4164 Generator loss: 0.7460 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.4282 Generator loss: 0.8461 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.4107 Generator loss: 0.7636
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [07:41<07:12, 7.01batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.4072 Generator loss: 0.8941 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.4425 Generator loss: 0.8638 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.4225 Generator loss: 0.6670 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.3942 Generator loss: 0.8384 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4196 Generator loss: 0.8091 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.4161 Generator loss: 0.6972 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.3853 Generator loss: 0.8171 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.3978 Generator loss: 0.7147 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.4107 Generator loss: 0.7713 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.4332 Generator loss: 0.7188
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [07:55<06:57, 7.01batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.4240 Generator loss: 0.7278 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.4850 Generator loss: 1.1613 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.4141 Generator loss: 0.7688 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.3958 Generator loss: 0.7042 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3881 Generator loss: 0.7879 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.4102 Generator loss: 0.7682 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.4523 Generator loss: 0.6456 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.4317 Generator loss: 0.8025 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.4060 Generator loss: 0.9406 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.3927 Generator loss: 0.8653
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [08:10<06:44, 7.00batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.3948 Generator loss: 0.7316 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.4281 Generator loss: 0.7513 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.4323 Generator loss: 0.7222 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.3982 Generator loss: 0.8426 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.3822 Generator loss: 0.7181 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.4190 Generator loss: 0.8883 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.4152 Generator loss: 0.8701 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.4010 Generator loss: 0.8235 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.4055 Generator loss: 0.7918 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.4010 Generator loss: 0.7239
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [08:24<06:29, 7.02batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.3916 Generator loss: 0.8231 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.4238 Generator loss: 0.7482 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.4047 Generator loss: 0.8261 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.4003 Generator loss: 0.7606 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.3891 Generator loss: 0.7478 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.3960 Generator loss: 0.7126 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3872 Generator loss: 0.7359 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.4375 Generator loss: 0.8619 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.4499 Generator loss: 0.6755 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.3845 Generator loss: 0.7685
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [08:38<06:12, 7.06batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.3830 Generator loss: 0.7770 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.4317 Generator loss: 0.8431 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.4084 Generator loss: 0.7033 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.4045 Generator loss: 0.7688 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.4312 Generator loss: 0.7076 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.4310 Generator loss: 0.8110 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.4061 Generator loss: 0.8852 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.4013 Generator loss: 0.7571 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.3789 Generator loss: 0.7369 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.4032 Generator loss: 0.8670
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [08:51<05:55, 7.13batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.4196 Generator loss: 0.8475 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.4094 Generator loss: 0.7437 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.4051 Generator loss: 0.7196 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.4117 Generator loss: 0.8583 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.4246 Generator loss: 0.6427 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.4547 Generator loss: 0.7178 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.4104 Generator loss: 0.7265 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.4173 Generator loss: 0.8011 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.3955 Generator loss: 0.9353 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.4076 Generator loss: 0.6708
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [09:07<05:49, 6.95batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.4154 Generator loss: 0.7540 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.3903 Generator loss: 0.7260 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.4116 Generator loss: 0.7176 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.3908 Generator loss: 0.8777 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.4076 Generator loss: 0.7832 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.4361 Generator loss: 0.7985 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.4143 Generator loss: 0.8411 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.4125 Generator loss: 0.8185 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.3877 Generator loss: 0.7716 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.4020 Generator loss: 0.8172
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [09:20<05:29, 7.08batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.4248 Generator loss: 0.6781 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.3971 Generator loss: 0.8456 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.4064 Generator loss: 0.7825 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.3818 Generator loss: 0.7260 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.4114 Generator loss: 0.8748 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.4388 Generator loss: 0.8505 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.4003 Generator loss: 0.7799 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.4339 Generator loss: 0.8694 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.4039 Generator loss: 0.7416 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.4038 Generator loss: 0.7255
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [09:34<05:13, 7.12batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.3902 Generator loss: 0.7501 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.4153 Generator loss: 0.7374 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.3987 Generator loss: 0.7314 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.4052 Generator loss: 0.8622 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.4171 Generator loss: 0.8476 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.3964 Generator loss: 0.7810 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.3990 Generator loss: 0.8907 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.3705 Generator loss: 0.7205 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.4338 Generator loss: 0.7447 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.4116 Generator loss: 0.8857
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.3907 Generator loss: 0.7260 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.3985 Generator loss: 0.8788 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.3991 Generator loss: 0.7809 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.4179 Generator loss: 0.7838 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.4001 Generator loss: 0.7294 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.3742 Generator loss: 0.8446 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.3984 Generator loss: 0.7174 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.4209 Generator loss: 0.7436 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.3956 Generator loss: 0.8392 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.4011 Generator loss: 0.7032
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.3757 Generator loss: 0.8378 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.4043 Generator loss: 0.6443 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3809 Generator loss: 0.7745 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.4078 Generator loss: 0.7605 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.4046 Generator loss: 0.7710 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.4434 Generator loss: 0.7068 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.3900 Generator loss: 0.7033 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.3921 Generator loss: 0.8545 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.3974 Generator loss: 0.6689 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.4285 Generator loss: 0.6341
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Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.3969 Generator loss: 0.8106 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.4089 Generator loss: 0.8441 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.4102 Generator loss: 0.7189 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.4071 Generator loss: 0.7548 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.4033 Generator loss: 0.7488 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.3926 Generator loss: 0.7635 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.4206 Generator loss: 0.7604 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.3991 Generator loss: 0.7538 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.3948 Generator loss: 0.7509 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.4142 Generator loss: 0.7085
Batches: 73%|████████████████████████████████████████████████████▎ | 4600/6331 [10:46<04:05, 7.04batch/s]
Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.3848 Generator loss: 0.7464 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.3838 Generator loss: 0.7882 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.4270 Generator loss: 0.9124 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.4018 Generator loss: 0.7520 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.4003 Generator loss: 0.7976 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.4006 Generator loss: 0.7012 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.4096 Generator loss: 0.8288 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.3891 Generator loss: 0.7098 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.4082 Generator loss: 0.7147 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.4066 Generator loss: 0.7001
Batches: 74%|█████████████████████████████████████████████████████▍ | 4700/6331 [11:01<03:55, 6.93batch/s]
Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.3889 Generator loss: 0.6725 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3787 Generator loss: 0.8030 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3988 Generator loss: 0.8128 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.3918 Generator loss: 0.7260 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.4020 Generator loss: 0.7983 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.4057 Generator loss: 0.7549 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.3969 Generator loss: 0.7736 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.3888 Generator loss: 0.8304 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.3891 Generator loss: 0.8338 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.3797 Generator loss: 0.7682
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [11:15<03:37, 7.04batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.4246 Generator loss: 0.7838 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.4449 Generator loss: 0.7874 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.4105 Generator loss: 0.7340 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.3802 Generator loss: 0.7202 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.4290 Generator loss: 0.8338 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.4073 Generator loss: 0.7588 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3953 Generator loss: 0.8229 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.4094 Generator loss: 0.7316 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.4061 Generator loss: 0.8548 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.4323 Generator loss: 0.6844
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [11:29<03:25, 6.95batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.4134 Generator loss: 0.7451 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.4159 Generator loss: 0.8191 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.4108 Generator loss: 0.7982 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.3991 Generator loss: 0.7864 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.3914 Generator loss: 0.7792 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.4316 Generator loss: 0.7524 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.3990 Generator loss: 0.7536 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.4063 Generator loss: 0.6916 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.4074 Generator loss: 0.7530 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.3968 Generator loss: 0.8551
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [11:43<03:09, 7.02batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.4103 Generator loss: 0.6685 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.4029 Generator loss: 0.8076 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.3943 Generator loss: 0.7797 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.4095 Generator loss: 0.8948 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.4112 Generator loss: 0.7044 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.3950 Generator loss: 0.8186 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.3902 Generator loss: 0.8603 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.3954 Generator loss: 0.7540 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.4061 Generator loss: 0.6912 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.4024 Generator loss: 0.7366
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [11:57<02:52, 7.14batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.4014 Generator loss: 0.8293 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.3985 Generator loss: 0.7938 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.3971 Generator loss: 0.7237 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.3859 Generator loss: 0.7839 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.3858 Generator loss: 0.8931 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3972 Generator loss: 0.7431 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.3944 Generator loss: 0.7151 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.3918 Generator loss: 0.8913 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.3910 Generator loss: 0.7114 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.4105 Generator loss: 0.6988
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [12:10<02:36, 7.23batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.4129 Generator loss: 0.7027 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.4270 Generator loss: 0.8204 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.3922 Generator loss: 0.7648 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.4245 Generator loss: 0.8440 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.3925 Generator loss: 0.7961 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.4047 Generator loss: 0.8835 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.3969 Generator loss: 0.7519 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.4020 Generator loss: 0.7916 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.4063 Generator loss: 0.8409 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.4006 Generator loss: 0.7190
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [12:24<02:22, 7.25batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.3990 Generator loss: 0.7284 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3964 Generator loss: 0.8664 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3932 Generator loss: 0.8401 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.3885 Generator loss: 0.7063 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.3829 Generator loss: 0.7886 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.3957 Generator loss: 0.7852 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3838 Generator loss: 0.7376 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.4088 Generator loss: 0.7482 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3859 Generator loss: 0.8526 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.3873 Generator loss: 0.8724
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [12:37<02:07, 7.30batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3722 Generator loss: 0.8144 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3821 Generator loss: 0.7670 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3990 Generator loss: 0.7421 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3892 Generator loss: 0.8738 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.3926 Generator loss: 0.7596 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3890 Generator loss: 0.7310 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3807 Generator loss: 0.8843 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.3994 Generator loss: 0.7245 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.4113 Generator loss: 0.7414 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.4011 Generator loss: 0.8215
Batches: 87%|██████████████████████████████████████████████████████████████▌ | 5500/6331 [12:52<01:55, 7.20batch/s]
Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.4070 Generator loss: 0.7816 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3996 Generator loss: 0.7368 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3878 Generator loss: 0.8286 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.3807 Generator loss: 0.7725 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3962 Generator loss: 0.7151 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.3822 Generator loss: 0.8371 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3881 Generator loss: 0.8926 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.3749 Generator loss: 0.8021 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.4077 Generator loss: 0.8244 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.4036 Generator loss: 0.8225
Batches: 88%|███████████████████████████████████████████████████████████████▋ | 5600/6331 [13:07<01:45, 6.95batch/s]
Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.4013 Generator loss: 0.7334 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3826 Generator loss: 0.7482 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3903 Generator loss: 0.7673 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3833 Generator loss: 0.7669 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.3884 Generator loss: 0.8309 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3685 Generator loss: 0.7921 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3902 Generator loss: 0.7781 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.3844 Generator loss: 0.7485 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.3883 Generator loss: 0.7635 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3703 Generator loss: 0.8258
Batches: 90%|████████████████████████████████████████████████████████████████▊ | 5700/6331 [13:21<01:29, 7.02batch/s]
Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3821 Generator loss: 0.8080 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.3808 Generator loss: 0.7469 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.4088 Generator loss: 0.7373 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.3952 Generator loss: 0.8104 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.4159 Generator loss: 0.6995 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.3876 Generator loss: 0.7504 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.3933 Generator loss: 0.7329 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.3769 Generator loss: 0.7914 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3897 Generator loss: 0.7945 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.4055 Generator loss: 0.8189
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Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.3807 Generator loss: 0.8057 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.3976 Generator loss: 0.8884 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.3973 Generator loss: 0.7599 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.4028 Generator loss: 0.9308 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.3891 Generator loss: 0.7922 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.4016 Generator loss: 0.7077 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3814 Generator loss: 0.8354 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.3816 Generator loss: 0.7755 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.3882 Generator loss: 0.8168 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3854 Generator loss: 0.8256
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3819 Generator loss: 0.7973 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3795 Generator loss: 0.8114 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3938 Generator loss: 0.7889 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3849 Generator loss: 0.7344 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.4028 Generator loss: 0.7119 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.4006 Generator loss: 0.7581 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3942 Generator loss: 0.7800 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.3805 Generator loss: 0.7978 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.3888 Generator loss: 0.8781 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3829 Generator loss: 0.7691
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.3963 Generator loss: 0.8535 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3805 Generator loss: 0.7818 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3996 Generator loss: 0.6844 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.3947 Generator loss: 0.8159 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3862 Generator loss: 0.8018 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.4071 Generator loss: 0.7449 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.3894 Generator loss: 0.7280 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.3982 Generator loss: 0.7345 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.4048 Generator loss: 0.8767 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3846 Generator loss: 0.7434
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.3758 Generator loss: 0.7918 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.3841 Generator loss: 0.7486 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3965 Generator loss: 0.8211 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.4099 Generator loss: 0.9408 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.4191 Generator loss: 0.6361 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.4137 Generator loss: 0.7785 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.3852 Generator loss: 0.7859 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.3797 Generator loss: 0.8496 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3767 Generator loss: 0.8477 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3931 Generator loss: 0.7898
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [14:32<00:18, 7.00batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.3980 Generator loss: 0.7699 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3828 Generator loss: 0.7986 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3908 Generator loss: 0.6961 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3701 Generator loss: 0.8850 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.3680 Generator loss: 0.8275 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3992 Generator loss: 0.7240 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3849 Generator loss: 0.8717 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3816 Generator loss: 0.8029 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3779 Generator loss: 0.8123 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3926 Generator loss: 0.8907
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [14:46<00:04, 7.12batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.3868 Generator loss: 0.7783 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.3822 Generator loss: 0.8259 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3940 Generator loss: 0.8244
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [14:50<00:00, 890.46s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.002
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 5.4785 Generator loss: 0.0145 Epoch 0/1... Batch 20/6331... Discriminator loss: 3.1037 Generator loss: 0.2022 Epoch 0/1... Batch 30/6331... Discriminator loss: 1.5078 Generator loss: 3.5222 Epoch 0/1... Batch 40/6331... Discriminator loss: 1.8756 Generator loss: 0.3056 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.4507 Generator loss: 0.6708 Epoch 0/1... Batch 60/6331... Discriminator loss: 2.0680 Generator loss: 3.3547 Epoch 0/1... Batch 70/6331... Discriminator loss: 1.1757 Generator loss: 0.8846 Epoch 0/1... Batch 80/6331... Discriminator loss: 1.7818 Generator loss: 0.3975 Epoch 0/1... Batch 90/6331... Discriminator loss: 1.9203 Generator loss: 0.4779 Epoch 0/1... Batch 100/6331... Discriminator loss: 1.3721 Generator loss: 1.3006
Batches: 2%|█▏ | 100/6331 [00:14<15:02, 6.90batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 2.1100 Generator loss: 2.6391 Epoch 0/1... Batch 120/6331... Discriminator loss: 1.0850 Generator loss: 1.1347 Epoch 0/1... Batch 130/6331... Discriminator loss: 1.2320 Generator loss: 1.1427 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.9154 Generator loss: 0.4311 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.6456 Generator loss: 0.6091 Epoch 0/1... Batch 160/6331... Discriminator loss: 1.3764 Generator loss: 0.5449 Epoch 0/1... Batch 170/6331... Discriminator loss: 1.9273 Generator loss: 1.0420 Epoch 0/1... Batch 180/6331... Discriminator loss: 2.5397 Generator loss: 0.1762 Epoch 0/1... Batch 190/6331... Discriminator loss: 1.8594 Generator loss: 0.7574 Epoch 0/1... Batch 200/6331... Discriminator loss: 1.3051 Generator loss: 0.6759
Batches: 3%|██▎ | 200/6331 [00:28<14:34, 7.01batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.8203 Generator loss: 0.5784 Epoch 0/1... Batch 220/6331... Discriminator loss: 2.0253 Generator loss: 1.1097 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.8859 Generator loss: 0.6231 Epoch 0/1... Batch 240/6331... Discriminator loss: 1.9620 Generator loss: 0.4044 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.4035 Generator loss: 0.9282 Epoch 0/1... Batch 260/6331... Discriminator loss: 1.1818 Generator loss: 0.9234 Epoch 0/1... Batch 270/6331... Discriminator loss: 2.4885 Generator loss: 0.4937 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.7995 Generator loss: 1.0746 Epoch 0/1... Batch 290/6331... Discriminator loss: 2.1149 Generator loss: 1.3782 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.3965 Generator loss: 0.7276
Batches: 5%|███▍ | 300/6331 [00:42<14:15, 7.05batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.6824 Generator loss: 0.4958 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.6539 Generator loss: 0.9383 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.6468 Generator loss: 0.5177 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.5757 Generator loss: 0.4954 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.6905 Generator loss: 0.5806 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.7350 Generator loss: 0.4691 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.2261 Generator loss: 0.8629 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.4403 Generator loss: 0.6781 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.4816 Generator loss: 0.6680 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.5251 Generator loss: 0.7345
Batches: 6%|████▌ | 400/6331 [00:55<13:47, 7.17batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.3398 Generator loss: 0.9800 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.2415 Generator loss: 0.7549 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.4504 Generator loss: 0.8302 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.3993 Generator loss: 0.7752 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.5410 Generator loss: 0.7830 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.5340 Generator loss: 0.6813 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.6678 Generator loss: 0.4724 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.5147 Generator loss: 0.5970 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.7731 Generator loss: 0.9161 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.6655 Generator loss: 0.5698
Batches: 8%|█████▊ | 500/6331 [01:09<13:27, 7.22batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.4102 Generator loss: 0.7118 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.5782 Generator loss: 0.8086 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.5106 Generator loss: 0.7364 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.3035 Generator loss: 0.9016 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.4435 Generator loss: 0.9248 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.4184 Generator loss: 0.6294 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.3414 Generator loss: 0.7565 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.4822 Generator loss: 0.7554 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.4856 Generator loss: 0.6337 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.5225 Generator loss: 0.7515
Batches: 9%|██████▉ | 600/6331 [01:23<13:22, 7.15batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.3645 Generator loss: 0.7663 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.4181 Generator loss: 0.7817 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.4087 Generator loss: 0.8593 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.5228 Generator loss: 0.7267 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.4235 Generator loss: 0.7614 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.4611 Generator loss: 0.9028 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.4396 Generator loss: 0.7613 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.4631 Generator loss: 0.8910 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.5109 Generator loss: 0.9115 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.5835 Generator loss: 0.6110
Batches: 11%|████████ | 700/6331 [01:37<13:04, 7.17batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.5556 Generator loss: 0.6940 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.5851 Generator loss: 0.6734 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.4037 Generator loss: 0.6884 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.5912 Generator loss: 0.5759 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.3493 Generator loss: 1.1394 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.3544 Generator loss: 0.7988 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.4470 Generator loss: 0.7187 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.3541 Generator loss: 0.7360 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.4936 Generator loss: 0.8309 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.4669 Generator loss: 0.8257
Batches: 13%|█████████▏ | 800/6331 [01:51<12:54, 7.14batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.5377 Generator loss: 0.6249 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.5879 Generator loss: 0.6793 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.4583 Generator loss: 0.8734 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.3445 Generator loss: 0.8125 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.4645 Generator loss: 0.7608 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.3824 Generator loss: 0.9079 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.4926 Generator loss: 0.6164 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.5338 Generator loss: 0.9245 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.5977 Generator loss: 0.9574 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.5118 Generator loss: 0.5517
Batches: 14%|██████████▍ | 900/6331 [02:05<12:34, 7.20batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.4349 Generator loss: 0.8191 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.3638 Generator loss: 0.8880 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.4962 Generator loss: 0.7921 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.3572 Generator loss: 0.7586 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.6041 Generator loss: 0.5142 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.3930 Generator loss: 0.8362 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.3249 Generator loss: 0.8692 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.5332 Generator loss: 0.5877 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.3610 Generator loss: 0.7264 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.4786 Generator loss: 0.7161
Batches: 16%|███████████▎ | 1000/6331 [02:18<12:14, 7.26batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.3712 Generator loss: 0.7698 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.4786 Generator loss: 0.7699 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.5091 Generator loss: 0.7302 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.4996 Generator loss: 0.7371 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.3137 Generator loss: 1.0486 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.4217 Generator loss: 0.6841 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.4736 Generator loss: 0.9324 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.4199 Generator loss: 0.6514 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.4991 Generator loss: 0.7126 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.5879 Generator loss: 0.8344
Batches: 17%|████████████▌ | 1100/6331 [02:32<11:56, 7.30batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.7027 Generator loss: 0.9369 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.4510 Generator loss: 0.6152 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.5151 Generator loss: 0.6996 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.5073 Generator loss: 0.7020 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.3323 Generator loss: 0.7635 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.5405 Generator loss: 0.7419 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.5885 Generator loss: 0.8452 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.4360 Generator loss: 0.7910 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.6760 Generator loss: 0.3732 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.4993 Generator loss: 0.6289
Batches: 19%|█████████████▋ | 1200/6331 [02:45<11:42, 7.30batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.7680 Generator loss: 0.3915 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.3818 Generator loss: 0.7519 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.5352 Generator loss: 0.6993 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.4570 Generator loss: 0.6567 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.5662 Generator loss: 0.6292 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.4840 Generator loss: 0.8351 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.4353 Generator loss: 0.7892 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.5086 Generator loss: 0.8928 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.4343 Generator loss: 0.7515 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.4217 Generator loss: 0.7400
Batches: 21%|██████████████▊ | 1300/6331 [03:00<11:38, 7.21batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.5274 Generator loss: 0.5842 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.5962 Generator loss: 0.6955 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.5567 Generator loss: 0.5699 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.4666 Generator loss: 0.7142 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.4870 Generator loss: 0.7878 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.3343 Generator loss: 0.7074 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.3833 Generator loss: 0.6479 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.4168 Generator loss: 0.8601 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.5446 Generator loss: 0.6278 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.7162 Generator loss: 0.5753
Batches: 22%|███████████████▉ | 1400/6331 [03:14<11:26, 7.19batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.5460 Generator loss: 0.6275 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.4580 Generator loss: 0.7785 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.3147 Generator loss: 0.8684 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.3520 Generator loss: 0.7639 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4829 Generator loss: 0.6683 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.3833 Generator loss: 0.9519 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.4133 Generator loss: 0.8412 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.4001 Generator loss: 0.8836 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4301 Generator loss: 0.6565 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.4533 Generator loss: 0.6802
Batches: 24%|█████████████████ | 1500/6331 [03:28<11:17, 7.13batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.4536 Generator loss: 0.6327 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.4404 Generator loss: 0.6506 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.4471 Generator loss: 0.6600 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.3865 Generator loss: 0.8323 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.4095 Generator loss: 0.7857 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.5187 Generator loss: 0.7263 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.3545 Generator loss: 0.8066 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.4724 Generator loss: 0.7154 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.3603 Generator loss: 0.8660 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.5263 Generator loss: 0.5791
Batches: 25%|██████████████████▏ | 1600/6331 [03:42<11:07, 7.09batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.5416 Generator loss: 0.6911 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.3653 Generator loss: 0.7032 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.3337 Generator loss: 0.7576 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.4095 Generator loss: 0.8439 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.3936 Generator loss: 0.7833 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.3462 Generator loss: 0.8430 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4780 Generator loss: 0.6042 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.4034 Generator loss: 0.7872 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.4923 Generator loss: 0.7566 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.4129 Generator loss: 0.6990
Batches: 27%|███████████████████▎ | 1700/6331 [03:56<10:52, 7.10batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.4521 Generator loss: 0.8650 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.4079 Generator loss: 0.7417 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.3902 Generator loss: 0.7402 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.4171 Generator loss: 0.8067 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.5765 Generator loss: 0.7358 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.5023 Generator loss: 0.7032 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4195 Generator loss: 0.9733 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.4872 Generator loss: 0.8992 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.5978 Generator loss: 0.5486 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.4890 Generator loss: 0.8039
Batches: 28%|████████████████████▍ | 1800/6331 [04:10<10:35, 7.12batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.4081 Generator loss: 0.9435 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.2961 Generator loss: 0.7341 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.3962 Generator loss: 0.8656 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.4764 Generator loss: 0.8754 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.5476 Generator loss: 0.7038 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.4577 Generator loss: 0.8086 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.4908 Generator loss: 0.5757 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.3440 Generator loss: 0.8403 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.4068 Generator loss: 0.7366 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4977 Generator loss: 0.7235
Batches: 30%|█████████████████████▌ | 1900/6331 [04:25<10:32, 7.01batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.3780 Generator loss: 0.8287 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.4774 Generator loss: 0.7974 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.4213 Generator loss: 0.7476 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.4552 Generator loss: 0.6673 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.4013 Generator loss: 0.7219 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.4471 Generator loss: 0.6609 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.4355 Generator loss: 0.6639 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.4326 Generator loss: 0.7149 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.4606 Generator loss: 0.7635 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.4154 Generator loss: 0.7561
Batches: 32%|██████████████████████▋ | 2000/6331 [04:39<10:17, 7.02batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.3957 Generator loss: 0.7453 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.5164 Generator loss: 0.6719 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.4271 Generator loss: 0.7100 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.4245 Generator loss: 0.7577 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.4767 Generator loss: 0.8206 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4608 Generator loss: 0.7268 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.4301 Generator loss: 0.7930 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.5929 Generator loss: 0.6690 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.5046 Generator loss: 0.6242 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.4342 Generator loss: 0.8479
Batches: 33%|███████████████████████▉ | 2100/6331 [04:53<09:55, 7.11batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.4110 Generator loss: 0.7373 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.3937 Generator loss: 0.8001 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.3300 Generator loss: 0.7522 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.4022 Generator loss: 0.8527 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4720 Generator loss: 0.6698 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.4285 Generator loss: 0.7193 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.4205 Generator loss: 0.8533 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.3295 Generator loss: 0.8205 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.3768 Generator loss: 0.7728 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.4755 Generator loss: 0.8110
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Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.4216 Generator loss: 0.7966 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.3953 Generator loss: 0.7284 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.5052 Generator loss: 0.7073 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.5375 Generator loss: 0.6304 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.5472 Generator loss: 0.7199 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.4572 Generator loss: 0.7208 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.3919 Generator loss: 0.8223 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4592 Generator loss: 0.7227 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.4468 Generator loss: 0.7711 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.4106 Generator loss: 0.7906
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Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.4172 Generator loss: 0.7939 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.4375 Generator loss: 0.7452 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.4618 Generator loss: 0.7489 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.3861 Generator loss: 0.7637 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.4116 Generator loss: 0.7548 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.4453 Generator loss: 0.7297 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.3903 Generator loss: 0.8429 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.3994 Generator loss: 0.8135 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4252 Generator loss: 0.7213 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.4195 Generator loss: 0.7667
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Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.4053 Generator loss: 0.6851 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.4230 Generator loss: 0.7761 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.4132 Generator loss: 0.7233 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.4424 Generator loss: 0.8060 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.4206 Generator loss: 0.7503 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.3958 Generator loss: 0.6830 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.4918 Generator loss: 0.6493 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.3896 Generator loss: 0.7554 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.4093 Generator loss: 0.8189 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.4347 Generator loss: 0.7161
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Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.3734 Generator loss: 0.8456 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.3674 Generator loss: 0.8410 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.4345 Generator loss: 0.7087 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.3700 Generator loss: 0.7998 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.3353 Generator loss: 0.7937 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.3677 Generator loss: 0.7439 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.3483 Generator loss: 0.7211 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.4507 Generator loss: 0.7262 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.5251 Generator loss: 0.6906 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.4393 Generator loss: 0.7076
Batches: 41%|█████████████████████████████▌ | 2600/6331 [06:03<08:50, 7.04batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.3985 Generator loss: 0.7784 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.4267 Generator loss: 0.8167 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.3958 Generator loss: 0.8551 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.3780 Generator loss: 0.6826 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.4372 Generator loss: 0.6881 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.3651 Generator loss: 0.7896 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.4139 Generator loss: 0.7877 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.3970 Generator loss: 0.8016 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.4159 Generator loss: 0.7326 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.4627 Generator loss: 0.7573
Batches: 43%|██████████████████████████████▋ | 2700/6331 [06:16<08:29, 7.12batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.3937 Generator loss: 0.6670 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.4176 Generator loss: 0.8211 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.3886 Generator loss: 0.8005 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.3722 Generator loss: 0.7539 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.3732 Generator loss: 0.7720 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.4765 Generator loss: 0.7193 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.3896 Generator loss: 0.7391 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.4510 Generator loss: 0.7396 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.5284 Generator loss: 0.6938 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.4336 Generator loss: 0.8063
Batches: 44%|███████████████████████████████▊ | 2800/6331 [06:30<08:09, 7.21batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.4316 Generator loss: 0.7838 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.4228 Generator loss: 0.7408 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.3844 Generator loss: 0.7070 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.4007 Generator loss: 0.7726 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.4807 Generator loss: 0.7067 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.4221 Generator loss: 0.6745 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.4507 Generator loss: 0.7299 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4224 Generator loss: 0.7717 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.4211 Generator loss: 0.7330 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.5109 Generator loss: 0.8434
Batches: 46%|████████████████████████████████▉ | 2900/6331 [06:44<07:55, 7.21batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4065 Generator loss: 0.8018 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4078 Generator loss: 0.7528 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.3991 Generator loss: 0.7072 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.3681 Generator loss: 0.7923 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.3881 Generator loss: 0.7614 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.4205 Generator loss: 0.7588 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.4309 Generator loss: 0.7624 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.4203 Generator loss: 0.7213 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.4079 Generator loss: 0.7360 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.3778 Generator loss: 0.7914
Batches: 47%|██████████████████████████████████ | 3000/6331 [06:57<07:38, 7.26batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.4237 Generator loss: 0.7746 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.4287 Generator loss: 0.6883 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.4467 Generator loss: 0.6926 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.4068 Generator loss: 0.7521 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.3709 Generator loss: 0.8092 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.4534 Generator loss: 0.7367 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.3968 Generator loss: 0.7855 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.4810 Generator loss: 0.7917 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.3225 Generator loss: 0.6890 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.5302 Generator loss: 0.6136
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [07:10<07:19, 7.36batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.3963 Generator loss: 0.6594 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.4143 Generator loss: 0.8232 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4524 Generator loss: 0.9755 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.4201 Generator loss: 0.7968 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.3874 Generator loss: 0.7813 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.4351 Generator loss: 0.7751 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.4309 Generator loss: 0.7980 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.4124 Generator loss: 0.7309 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.4253 Generator loss: 0.6750 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4173 Generator loss: 0.7212
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [07:24<07:02, 7.42batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4268 Generator loss: 0.7316 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4332 Generator loss: 0.8771 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.3775 Generator loss: 0.8612 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.3852 Generator loss: 0.7252 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.4105 Generator loss: 0.7630 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.4048 Generator loss: 0.7958 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.3995 Generator loss: 0.7678 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.3482 Generator loss: 0.9109 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.3822 Generator loss: 0.7981 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.3749 Generator loss: 0.7578
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [07:37<06:46, 7.46batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.3776 Generator loss: 0.8324 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.3882 Generator loss: 0.7951 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.3820 Generator loss: 0.7525 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.3744 Generator loss: 0.8554 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4152 Generator loss: 0.7091 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.3242 Generator loss: 0.7215 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.3369 Generator loss: 0.8453 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.3933 Generator loss: 0.7737 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.4175 Generator loss: 0.8202 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.4849 Generator loss: 0.6937
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [07:51<06:39, 7.34batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.4995 Generator loss: 0.7412 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.4431 Generator loss: 0.7004 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.3513 Generator loss: 0.8653 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.4269 Generator loss: 0.7437 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3643 Generator loss: 0.7133 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.4227 Generator loss: 0.7534 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.3722 Generator loss: 0.8477 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.3811 Generator loss: 0.7948 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.3829 Generator loss: 0.8169 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.3868 Generator loss: 0.7505
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [08:05<06:25, 7.34batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.3558 Generator loss: 0.7833 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.4161 Generator loss: 0.7362 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.3769 Generator loss: 0.8022 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.4043 Generator loss: 0.7890 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.4018 Generator loss: 0.7960 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.3700 Generator loss: 0.7948 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.3907 Generator loss: 0.7887 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.4091 Generator loss: 0.8046 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.4297 Generator loss: 0.7644 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.4266 Generator loss: 0.7878
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [08:18<06:08, 7.40batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.4274 Generator loss: 0.7736 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.4185 Generator loss: 0.7863 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.4290 Generator loss: 0.7417 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.3884 Generator loss: 0.7066 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.3838 Generator loss: 0.7933 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.3987 Generator loss: 0.7903 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3920 Generator loss: 0.7767 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.4563 Generator loss: 0.6856 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.4204 Generator loss: 0.6917 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.3793 Generator loss: 0.8067
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [08:31<05:51, 7.48batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.3925 Generator loss: 0.7814 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.4099 Generator loss: 0.7862 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.3874 Generator loss: 0.7914 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.3841 Generator loss: 0.8233 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.4107 Generator loss: 0.7816 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.4053 Generator loss: 0.7896 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.3819 Generator loss: 0.8129 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.3528 Generator loss: 0.7933 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.4282 Generator loss: 0.7620 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.4212 Generator loss: 0.7705
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [08:45<05:40, 7.42batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.3964 Generator loss: 0.7782 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.3920 Generator loss: 0.8104 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.4086 Generator loss: 0.7822 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.4341 Generator loss: 0.7369 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.3864 Generator loss: 0.7984 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.3949 Generator loss: 0.8172 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.3972 Generator loss: 0.7837 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.4043 Generator loss: 0.7306 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.4186 Generator loss: 0.8760 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.3758 Generator loss: 0.8001
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [08:58<05:24, 7.48batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.4170 Generator loss: 0.7451 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.3662 Generator loss: 0.7710 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.4033 Generator loss: 0.8023 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.3731 Generator loss: 0.7732 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.4050 Generator loss: 0.7707 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.4150 Generator loss: 0.7346 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.4132 Generator loss: 0.7845 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.3799 Generator loss: 0.7823 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.4002 Generator loss: 0.7594 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.4047 Generator loss: 0.7884
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [09:12<05:19, 7.29batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.4192 Generator loss: 0.7525 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.4001 Generator loss: 0.7855 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.4365 Generator loss: 0.7269 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.3918 Generator loss: 0.7649 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.4124 Generator loss: 0.7742 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.3668 Generator loss: 0.8223 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.4235 Generator loss: 0.7193 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.3787 Generator loss: 0.8302 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.4140 Generator loss: 0.7627 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.3969 Generator loss: 0.7534
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [09:26<05:07, 7.25batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.4001 Generator loss: 0.7938 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.4262 Generator loss: 0.8509 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.4358 Generator loss: 0.7998 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.3721 Generator loss: 0.7917 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.5501 Generator loss: 0.5193 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.4046 Generator loss: 0.8078 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.4550 Generator loss: 0.7316 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.4168 Generator loss: 0.7462 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.3966 Generator loss: 0.7953 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.4280 Generator loss: 0.7232
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.3942 Generator loss: 0.7599 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.3957 Generator loss: 0.7979 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.4321 Generator loss: 0.7155 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.4015 Generator loss: 0.7752 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.4153 Generator loss: 0.7394 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.3778 Generator loss: 0.7823 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.3697 Generator loss: 0.7568 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.4230 Generator loss: 0.7054 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.3866 Generator loss: 0.8173 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.3898 Generator loss: 0.7465
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.4189 Generator loss: 0.7360 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.4050 Generator loss: 0.7423 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3932 Generator loss: 0.7765 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.4100 Generator loss: 0.7517 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.3903 Generator loss: 0.7680 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.3702 Generator loss: 0.8121 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.3871 Generator loss: 0.7475 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.3907 Generator loss: 0.8252 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.4130 Generator loss: 0.7641 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.3659 Generator loss: 0.7719
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Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.4081 Generator loss: 0.7758 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.3830 Generator loss: 0.7628 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.3736 Generator loss: 0.7803 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.3824 Generator loss: 0.7662 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.4060 Generator loss: 0.7572 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.4086 Generator loss: 0.7571 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.3707 Generator loss: 0.7803 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.3991 Generator loss: 0.7821 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.3835 Generator loss: 0.8678 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.4731 Generator loss: 0.8485
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Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.3330 Generator loss: 0.5935 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.3887 Generator loss: 0.7721 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.5286 Generator loss: 0.6720 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.4472 Generator loss: 0.7834 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.2183 Generator loss: 0.8118 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.5263 Generator loss: 0.5336 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.4122 Generator loss: 0.8063 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.4592 Generator loss: 0.7433 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.4126 Generator loss: 0.7362 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.4087 Generator loss: 0.7576
Batches: 74%|█████████████████████████████████████████████████████▍ | 4700/6331 [10:49<03:43, 7.28batch/s]
Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.4647 Generator loss: 0.7418 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3925 Generator loss: 0.7967 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3906 Generator loss: 0.8108 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.3842 Generator loss: 0.7742 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.3670 Generator loss: 0.7676 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.4111 Generator loss: 0.7421 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.3923 Generator loss: 0.8216 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.3958 Generator loss: 0.7641 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.3668 Generator loss: 0.7663 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.3949 Generator loss: 0.7390
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [11:03<03:30, 7.28batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.3854 Generator loss: 0.7780 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.3932 Generator loss: 0.7774 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.3819 Generator loss: 0.7865 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.4136 Generator loss: 0.7096 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.3957 Generator loss: 0.7783 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.4439 Generator loss: 0.7248 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3690 Generator loss: 0.7980 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.4107 Generator loss: 0.7605 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.4256 Generator loss: 0.7069 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.3822 Generator loss: 0.7773
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [11:16<03:15, 7.31batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.3828 Generator loss: 0.7836 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.4210 Generator loss: 0.7560 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.3453 Generator loss: 0.8259 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.3626 Generator loss: 0.7825 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.3878 Generator loss: 0.7758 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.3938 Generator loss: 0.7867 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.3907 Generator loss: 0.7920 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.4185 Generator loss: 0.7619 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.3888 Generator loss: 0.7759 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.3909 Generator loss: 0.7795
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [11:30<03:01, 7.33batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.3889 Generator loss: 0.7731 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.4095 Generator loss: 0.7404 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.3638 Generator loss: 0.7681 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.3977 Generator loss: 0.7967 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.3845 Generator loss: 0.7865 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.3908 Generator loss: 0.7734 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.3919 Generator loss: 0.7902 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.4004 Generator loss: 0.7678 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.3871 Generator loss: 0.7794 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.3767 Generator loss: 0.8157
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [11:44<02:49, 7.24batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.3905 Generator loss: 0.7871 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.3934 Generator loss: 0.7276 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.4116 Generator loss: 0.7462 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.3863 Generator loss: 0.7832 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.4263 Generator loss: 0.8481 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3923 Generator loss: 0.7671 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.4032 Generator loss: 0.7558 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.4250 Generator loss: 0.7873 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.3716 Generator loss: 0.8087 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.3927 Generator loss: 0.7842
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [11:57<02:34, 7.34batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.4031 Generator loss: 0.7657 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.3913 Generator loss: 0.8097 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.3748 Generator loss: 0.7809 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.3673 Generator loss: 0.7836 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.4261 Generator loss: 0.7654 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.3877 Generator loss: 0.7688 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.3936 Generator loss: 0.7800 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.3633 Generator loss: 0.7974 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.3810 Generator loss: 0.8122 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.3932 Generator loss: 0.7695
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [12:11<02:21, 7.27batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.4026 Generator loss: 0.7725 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3860 Generator loss: 0.7749 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3802 Generator loss: 0.8130 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.3891 Generator loss: 0.7891 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.3985 Generator loss: 0.7768 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.3825 Generator loss: 0.7838 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3795 Generator loss: 0.8037 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.3790 Generator loss: 0.7972 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3670 Generator loss: 0.7731 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.3717 Generator loss: 0.7839
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [12:25<02:07, 7.32batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3757 Generator loss: 0.7561 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3861 Generator loss: 0.7951 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3990 Generator loss: 0.7809 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3808 Generator loss: 0.7980 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.3723 Generator loss: 0.7736 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3870 Generator loss: 0.7694 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3060 Generator loss: 0.8602 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.4049 Generator loss: 0.7725 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.3716 Generator loss: 0.7937 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.4346 Generator loss: 0.7268
Batches: 87%|██████████████████████████████████████████████████████████████▌ | 5500/6331 [12:38<01:53, 7.30batch/s]
Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.4108 Generator loss: 0.7794 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3955 Generator loss: 0.7727 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3882 Generator loss: 0.7780 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.3933 Generator loss: 0.7963 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3799 Generator loss: 0.7645 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.3934 Generator loss: 0.7953 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3546 Generator loss: 0.8395 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.4003 Generator loss: 0.7739 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.3840 Generator loss: 0.7868 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.4041 Generator loss: 0.7600
Batches: 88%|███████████████████████████████████████████████████████████████▋ | 5600/6331 [12:52<01:40, 7.29batch/s]
Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.3970 Generator loss: 0.7686 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3772 Generator loss: 0.7938 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3820 Generator loss: 0.7791 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3856 Generator loss: 0.7791 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.3369 Generator loss: 0.8355 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3153 Generator loss: 0.8394 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3808 Generator loss: 0.9652 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.4070 Generator loss: 0.7581 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.3965 Generator loss: 0.7878 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3923 Generator loss: 0.7952
Batches: 90%|████████████████████████████████████████████████████████████████▊ | 5700/6331 [13:06<01:25, 7.34batch/s]
Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3966 Generator loss: 0.7761 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.3567 Generator loss: 0.7943 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.3992 Generator loss: 0.7557 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.5247 Generator loss: 0.5302 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.4299 Generator loss: 0.7614 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.4350 Generator loss: 0.7656 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.3930 Generator loss: 0.8085 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.4019 Generator loss: 0.7915 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3687 Generator loss: 0.7840 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.3950 Generator loss: 0.7637
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Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.3997 Generator loss: 0.7840 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.3887 Generator loss: 0.7532 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.3825 Generator loss: 0.7857 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.3824 Generator loss: 0.8025 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.3844 Generator loss: 0.7782 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.3742 Generator loss: 0.7971 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3785 Generator loss: 0.7979 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.4026 Generator loss: 0.7621 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.3965 Generator loss: 0.7716 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3855 Generator loss: 0.7653
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3800 Generator loss: 0.7749 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3634 Generator loss: 0.8167 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3916 Generator loss: 0.7811 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3769 Generator loss: 0.8052 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.3968 Generator loss: 0.7690 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.4065 Generator loss: 0.7867 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3858 Generator loss: 0.7708 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.3810 Generator loss: 0.7953 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.3824 Generator loss: 0.7623 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3785 Generator loss: 0.7679
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.4068 Generator loss: 0.7537 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3762 Generator loss: 0.8144 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3948 Generator loss: 0.7807 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.3548 Generator loss: 0.7948 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3860 Generator loss: 0.7819 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.3855 Generator loss: 0.8065 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.4001 Generator loss: 0.7622 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.3965 Generator loss: 0.7953 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.3846 Generator loss: 0.7916 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3713 Generator loss: 0.7928
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.3917 Generator loss: 0.7902 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.3744 Generator loss: 0.7725 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3922 Generator loss: 0.7840 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.3717 Generator loss: 0.7973 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.3882 Generator loss: 0.7877 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.3858 Generator loss: 0.7933 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.3746 Generator loss: 0.7679 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.3913 Generator loss: 0.7943 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3969 Generator loss: 0.7815 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3763 Generator loss: 0.7945
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [14:15<00:18, 7.24batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.3952 Generator loss: 0.7737 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3958 Generator loss: 0.7822 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3730 Generator loss: 0.7785 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3999 Generator loss: 0.7831 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.4016 Generator loss: 0.7701 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3816 Generator loss: 0.7833 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3869 Generator loss: 0.7854 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3847 Generator loss: 0.7975 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3589 Generator loss: 0.7997 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3881 Generator loss: 0.7903
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [14:29<00:04, 7.26batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.3937 Generator loss: 0.7800 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.4001 Generator loss: 0.7702 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3858 Generator loss: 0.7886
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [14:33<00:00, 873.21s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.002
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 3.0599 Generator loss: 0.2022 Epoch 0/1... Batch 20/6331... Discriminator loss: 1.6020 Generator loss: 1.0375 Epoch 0/1... Batch 30/6331... Discriminator loss: 2.0318 Generator loss: 0.3676 Epoch 0/1... Batch 40/6331... Discriminator loss: 2.2556 Generator loss: 3.6343 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.2799 Generator loss: 0.8415 Epoch 0/1... Batch 60/6331... Discriminator loss: 1.4532 Generator loss: 3.6584 Epoch 0/1... Batch 70/6331... Discriminator loss: 1.1448 Generator loss: 1.1149 Epoch 0/1... Batch 80/6331... Discriminator loss: 4.1130 Generator loss: 1.9821 Epoch 0/1... Batch 90/6331... Discriminator loss: 1.7820 Generator loss: 0.5212 Epoch 0/1... Batch 100/6331... Discriminator loss: 1.3914 Generator loss: 0.9032
Batches: 2%|█▏ | 100/6331 [00:20<21:13, 4.89batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 2.1552 Generator loss: 0.6223 Epoch 0/1... Batch 120/6331... Discriminator loss: 1.6587 Generator loss: 0.4743 Epoch 0/1... Batch 130/6331... Discriminator loss: 2.2416 Generator loss: 0.2690 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.8161 Generator loss: 0.4261 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.8663 Generator loss: 1.2373 Epoch 0/1... Batch 160/6331... Discriminator loss: 1.7989 Generator loss: 0.5121 Epoch 0/1... Batch 170/6331... Discriminator loss: 2.2521 Generator loss: 0.6004 Epoch 0/1... Batch 180/6331... Discriminator loss: 1.8970 Generator loss: 0.6565 Epoch 0/1... Batch 190/6331... Discriminator loss: 1.6649 Generator loss: 0.5746 Epoch 0/1... Batch 200/6331... Discriminator loss: 3.0268 Generator loss: 0.2713
Batches: 3%|██▎ | 200/6331 [00:40<20:38, 4.95batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.4654 Generator loss: 1.1791 Epoch 0/1... Batch 220/6331... Discriminator loss: 1.8661 Generator loss: 1.2836 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.5679 Generator loss: 0.5172 Epoch 0/1... Batch 240/6331... Discriminator loss: 1.6973 Generator loss: 0.6153 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.6238 Generator loss: 0.9990 Epoch 0/1... Batch 260/6331... Discriminator loss: 1.6379 Generator loss: 1.0291 Epoch 0/1... Batch 270/6331... Discriminator loss: 1.9137 Generator loss: 0.4852 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.7044 Generator loss: 0.7043 Epoch 0/1... Batch 290/6331... Discriminator loss: 1.6377 Generator loss: 0.7749 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.5941 Generator loss: 0.6610
Batches: 5%|███▍ | 300/6331 [01:01<20:37, 4.87batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.8440 Generator loss: 0.6588 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.7761 Generator loss: 0.5778 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.6315 Generator loss: 0.6715 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.8651 Generator loss: 1.1667 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.7157 Generator loss: 0.3781 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.4067 Generator loss: 0.8118 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.9382 Generator loss: 0.5852 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.3596 Generator loss: 0.8081 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.5816 Generator loss: 0.6382 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.5895 Generator loss: 0.7250
Batches: 6%|████▌ | 400/6331 [01:21<20:03, 4.93batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.5304 Generator loss: 0.7694 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.6198 Generator loss: 0.6161 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.5929 Generator loss: 0.9247 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.5276 Generator loss: 0.6868 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.6165 Generator loss: 0.6713 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.4023 Generator loss: 0.9631 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.5503 Generator loss: 0.5960 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.4513 Generator loss: 0.7274 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.4405 Generator loss: 0.7560 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.4869 Generator loss: 0.7936
Batches: 8%|█████▊ | 500/6331 [01:41<19:43, 4.93batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.4750 Generator loss: 0.8107 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.5162 Generator loss: 0.6421 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.6059 Generator loss: 0.5170 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.5322 Generator loss: 0.6412 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.5242 Generator loss: 0.8479 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.6130 Generator loss: 0.4527 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.5566 Generator loss: 0.6003 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.5253 Generator loss: 0.6473 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.6102 Generator loss: 0.4875 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.5015 Generator loss: 0.6794
Batches: 9%|██████▉ | 600/6331 [02:02<19:37, 4.87batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.4789 Generator loss: 0.6402 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.5491 Generator loss: 0.6087 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.5298 Generator loss: 0.8812 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.6168 Generator loss: 0.6849 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.4269 Generator loss: 0.7742 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.6240 Generator loss: 0.7434 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.4024 Generator loss: 0.8158 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.6558 Generator loss: 0.6225 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.4859 Generator loss: 0.8364 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.4797 Generator loss: 0.9222
Batches: 11%|████████ | 700/6331 [02:21<18:56, 4.95batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.4854 Generator loss: 0.8272 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.4118 Generator loss: 0.7427 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.4807 Generator loss: 0.6613 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.4890 Generator loss: 0.6445 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.5758 Generator loss: 0.8956 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.4733 Generator loss: 0.6545 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.4984 Generator loss: 0.7210 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.5842 Generator loss: 0.7440 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.4774 Generator loss: 0.6900 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.5635 Generator loss: 0.8077
Batches: 13%|█████████▏ | 800/6331 [02:42<18:43, 4.92batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.3670 Generator loss: 0.7589 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.7766 Generator loss: 0.6751 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.4664 Generator loss: 0.7101 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.4340 Generator loss: 0.7340 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.4265 Generator loss: 1.0342 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.4741 Generator loss: 0.7583 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.6285 Generator loss: 0.6310 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.3650 Generator loss: 0.8752 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.5924 Generator loss: 0.6408 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.4855 Generator loss: 0.5941
Batches: 14%|██████████▍ | 900/6331 [03:02<18:17, 4.95batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.5339 Generator loss: 0.6931 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.5676 Generator loss: 0.7484 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.4710 Generator loss: 0.7317 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.4289 Generator loss: 0.6969 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.4728 Generator loss: 0.7284 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.4182 Generator loss: 0.9641 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.4948 Generator loss: 0.5590 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.5037 Generator loss: 0.7417 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.5329 Generator loss: 0.5618 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.4626 Generator loss: 0.7748
Batches: 16%|███████████▎ | 1000/6331 [03:23<18:18, 4.85batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.4508 Generator loss: 0.7520 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.4197 Generator loss: 0.7421 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.4563 Generator loss: 0.7178 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.5546 Generator loss: 0.6778 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.3906 Generator loss: 0.8115 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.4376 Generator loss: 0.6683 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.4643 Generator loss: 1.0243 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.4300 Generator loss: 0.6791 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.4539 Generator loss: 0.8585 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.4216 Generator loss: 0.6680
Batches: 17%|████████████▌ | 1100/6331 [03:43<17:48, 4.90batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.4546 Generator loss: 0.7391 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.5588 Generator loss: 0.7175 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.4761 Generator loss: 0.6682 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.6582 Generator loss: 0.5650 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.6194 Generator loss: 0.6456 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.6419 Generator loss: 0.5675 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.4732 Generator loss: 0.5331 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.6085 Generator loss: 0.6922 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.3875 Generator loss: 0.7699 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.3963 Generator loss: 0.8275
Batches: 19%|█████████████▋ | 1200/6331 [04:03<17:17, 4.95batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.3137 Generator loss: 0.8322 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.4234 Generator loss: 0.8287 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.5179 Generator loss: 0.7934 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.5373 Generator loss: 0.5216 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.4631 Generator loss: 0.6278 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.5032 Generator loss: 0.7294 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.3856 Generator loss: 0.7072 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.4806 Generator loss: 0.6973 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.4608 Generator loss: 0.9615 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.4481 Generator loss: 0.7602
Batches: 21%|██████████████▊ | 1300/6331 [04:23<16:51, 4.97batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.4883 Generator loss: 0.8028 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.3658 Generator loss: 0.8867 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.5346 Generator loss: 0.7422 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.3881 Generator loss: 0.8343 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.5551 Generator loss: 0.8093 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.4831 Generator loss: 0.7752 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.4447 Generator loss: 0.7330 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.4365 Generator loss: 0.6601 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.3777 Generator loss: 0.8351 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.4637 Generator loss: 0.7039
Batches: 22%|███████████████▉ | 1400/6331 [04:44<16:47, 4.90batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.4217 Generator loss: 0.7377 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.4660 Generator loss: 1.0586 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.4512 Generator loss: 0.6952 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.4858 Generator loss: 0.6966 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4459 Generator loss: 0.7781 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.4416 Generator loss: 0.8097 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.3844 Generator loss: 0.8983 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.4535 Generator loss: 0.9788 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4260 Generator loss: 0.6081 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.3890 Generator loss: 0.7938
Batches: 24%|█████████████████ | 1500/6331 [05:05<16:29, 4.88batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.4058 Generator loss: 0.8011 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.4293 Generator loss: 0.6647 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.4402 Generator loss: 0.6589 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.4017 Generator loss: 0.8244 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.3985 Generator loss: 0.7907 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.4538 Generator loss: 0.7162 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.4050 Generator loss: 0.9125 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.4541 Generator loss: 0.7296 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.4332 Generator loss: 0.8114 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.5108 Generator loss: 0.8024
Batches: 25%|██████████████████▏ | 1600/6331 [05:25<15:59, 4.93batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.4155 Generator loss: 0.7314 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.3573 Generator loss: 0.7409 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.4487 Generator loss: 0.7333 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.4359 Generator loss: 0.8847 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.4043 Generator loss: 0.8067 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.4153 Generator loss: 0.9421 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4190 Generator loss: 0.7374 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.3470 Generator loss: 0.7271 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.3960 Generator loss: 0.6960 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.4806 Generator loss: 0.6960
Batches: 27%|███████████████████▎ | 1700/6331 [05:45<15:37, 4.94batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.4811 Generator loss: 0.7732 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.5455 Generator loss: 0.9046 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.4186 Generator loss: 0.8388 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.4811 Generator loss: 0.9448 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.4532 Generator loss: 0.7316 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.4100 Generator loss: 0.7414 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4556 Generator loss: 0.7895 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.5375 Generator loss: 0.6875 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.5554 Generator loss: 0.5803 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.4364 Generator loss: 0.8062
Batches: 28%|████████████████████▍ | 1800/6331 [06:05<15:21, 4.92batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.4570 Generator loss: 0.8149 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.4017 Generator loss: 0.6887 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.4250 Generator loss: 0.6732 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.4254 Generator loss: 0.7639 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.4328 Generator loss: 0.6938 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.3998 Generator loss: 0.8071 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.4134 Generator loss: 0.6642 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.4263 Generator loss: 0.7370 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.4823 Generator loss: 0.7258 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4980 Generator loss: 0.7555
Batches: 30%|█████████████████████▌ | 1900/6331 [06:25<14:46, 5.00batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.4859 Generator loss: 0.8288 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.4806 Generator loss: 0.7232 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.3837 Generator loss: 0.8121 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.5233 Generator loss: 0.5168 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.4055 Generator loss: 0.7557 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.4089 Generator loss: 0.7872 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.3821 Generator loss: 0.7778 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.4318 Generator loss: 0.6660 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.3820 Generator loss: 0.7961 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.3967 Generator loss: 0.8699
Batches: 32%|██████████████████████▋ | 2000/6331 [06:45<14:33, 4.96batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.4225 Generator loss: 0.7802 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.4615 Generator loss: 0.6534 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.4827 Generator loss: 0.6359 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.4692 Generator loss: 0.7458 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.5201 Generator loss: 0.6739 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4603 Generator loss: 0.7760 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.4619 Generator loss: 0.8826 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.4121 Generator loss: 0.6684 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.3587 Generator loss: 0.7575 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.4578 Generator loss: 0.6544
Batches: 33%|███████████████████████▉ | 2100/6331 [07:09<14:55, 4.72batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.4574 Generator loss: 0.7029 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.4744 Generator loss: 0.6610 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.4181 Generator loss: 0.6739 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.4346 Generator loss: 0.7795 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4230 Generator loss: 0.8310 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.4399 Generator loss: 0.6822 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.3852 Generator loss: 0.7038 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.3930 Generator loss: 0.8288 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.4082 Generator loss: 0.7141 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.3847 Generator loss: 0.8076
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Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.4028 Generator loss: 0.8563 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.3907 Generator loss: 0.8895 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.3655 Generator loss: 0.7962 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.4185 Generator loss: 0.7211 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.4374 Generator loss: 0.7159 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.3937 Generator loss: 0.8131 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.3766 Generator loss: 0.8374 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4275 Generator loss: 0.7467 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.3731 Generator loss: 0.8724 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.4334 Generator loss: 0.7077
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Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.4016 Generator loss: 0.9586 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.4653 Generator loss: 0.8232 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.4489 Generator loss: 0.6521 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.4982 Generator loss: 0.7542 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.3956 Generator loss: 0.7032 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.3852 Generator loss: 0.7880 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.4707 Generator loss: 0.8472 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.3819 Generator loss: 0.7763 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4535 Generator loss: 0.6041 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.4100 Generator loss: 0.7844
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Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.4276 Generator loss: 0.7805 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.4326 Generator loss: 0.7606 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.3857 Generator loss: 0.7989 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.4294 Generator loss: 0.7409 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.4385 Generator loss: 0.7344 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.4055 Generator loss: 0.6875 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.3945 Generator loss: 0.7409 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.3910 Generator loss: 0.8110 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.3722 Generator loss: 0.8319 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.4092 Generator loss: 0.7083
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Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.3762 Generator loss: 0.9032 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.4175 Generator loss: 0.7896 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.3834 Generator loss: 0.7491 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.4152 Generator loss: 0.9096 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.4161 Generator loss: 0.7235 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.3868 Generator loss: 0.8351 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.4056 Generator loss: 0.8072 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.3910 Generator loss: 0.7654 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.3873 Generator loss: 0.8425 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.3919 Generator loss: 0.8606
Batches: 41%|█████████████████████████████▌ | 2600/6331 [08:51<12:38, 4.92batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.4262 Generator loss: 0.6658 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.4204 Generator loss: 0.7556 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.3855 Generator loss: 0.8218 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.4414 Generator loss: 0.8354 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.3873 Generator loss: 0.8422 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.4110 Generator loss: 0.7149 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.4479 Generator loss: 0.7882 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.4044 Generator loss: 0.7222 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.4130 Generator loss: 0.7404 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.4028 Generator loss: 0.7811
Batches: 43%|██████████████████████████████▋ | 2700/6331 [09:11<12:10, 4.97batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.3765 Generator loss: 0.8209 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.4097 Generator loss: 0.7087 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.4113 Generator loss: 0.7192 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.4960 Generator loss: 0.6508 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.4587 Generator loss: 0.7781 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.4286 Generator loss: 0.8354 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.4049 Generator loss: 0.7019 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.3964 Generator loss: 0.7261 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.3629 Generator loss: 0.8064 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.4145 Generator loss: 0.8121
Batches: 44%|███████████████████████████████▊ | 2800/6331 [09:29<11:36, 5.07batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.3774 Generator loss: 0.8414 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.3967 Generator loss: 0.9030 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.4118 Generator loss: 0.7789 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.3759 Generator loss: 0.7329 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.3889 Generator loss: 0.7575 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.4155 Generator loss: 0.8319 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.4225 Generator loss: 0.8085 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4006 Generator loss: 0.7639 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.4438 Generator loss: 0.8247 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.4030 Generator loss: 0.7582
Batches: 46%|████████████████████████████████▉ | 2900/6331 [09:48<11:06, 5.15batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4390 Generator loss: 0.8836 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4153 Generator loss: 0.6562 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.3871 Generator loss: 0.7916 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.4375 Generator loss: 0.7246 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.4162 Generator loss: 0.7543 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.4128 Generator loss: 0.7473 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.4113 Generator loss: 0.7362 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.3753 Generator loss: 0.7268 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.4221 Generator loss: 0.6931 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.3849 Generator loss: 0.7923
Batches: 47%|██████████████████████████████████ | 3000/6331 [10:08<10:47, 5.15batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.3930 Generator loss: 0.7773 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.3857 Generator loss: 0.7569 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.5305 Generator loss: 0.6106 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.4168 Generator loss: 0.7010 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.4279 Generator loss: 0.6734 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.4450 Generator loss: 0.7161 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.4433 Generator loss: 0.7296 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.4166 Generator loss: 0.7380 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.4312 Generator loss: 0.7545 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.3830 Generator loss: 0.7622
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [10:27<10:26, 5.16batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.3834 Generator loss: 0.8017 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.3927 Generator loss: 0.7143 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4076 Generator loss: 0.8465 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.4103 Generator loss: 0.7222 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.3856 Generator loss: 0.7840 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.3681 Generator loss: 0.7860 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.4008 Generator loss: 0.7476 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.3959 Generator loss: 0.7099 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.4071 Generator loss: 0.7300 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4025 Generator loss: 0.7156
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [10:47<10:13, 5.11batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4689 Generator loss: 0.6781 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4418 Generator loss: 0.7472 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.4029 Generator loss: 0.8017 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.3985 Generator loss: 0.7622 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.4276 Generator loss: 0.7572 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.4140 Generator loss: 0.8584 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.4119 Generator loss: 0.7641 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.4275 Generator loss: 0.7783 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.3770 Generator loss: 0.8043 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.3864 Generator loss: 0.8062
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [11:06<09:50, 5.13batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.3774 Generator loss: 0.8538 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.3944 Generator loss: 0.7767 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.4213 Generator loss: 0.7197 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.4142 Generator loss: 0.7450 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4086 Generator loss: 0.7398 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.4172 Generator loss: 0.7801 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.3856 Generator loss: 0.7787 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.4062 Generator loss: 0.7804 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.4006 Generator loss: 0.7772 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.4029 Generator loss: 0.8441
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [11:26<09:34, 5.10batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.3913 Generator loss: 0.7360 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.3659 Generator loss: 0.7793 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.4141 Generator loss: 0.7755 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.4063 Generator loss: 0.8046 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3912 Generator loss: 0.8062 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.3884 Generator loss: 0.8081 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.4139 Generator loss: 0.7505 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.4021 Generator loss: 0.8216 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.3901 Generator loss: 0.8044 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.3784 Generator loss: 0.7671
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [11:46<09:14, 5.10batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.4212 Generator loss: 0.7484 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.3842 Generator loss: 0.7466 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.3928 Generator loss: 0.8271 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.4468 Generator loss: 0.7008 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.3715 Generator loss: 0.8529 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.4107 Generator loss: 0.7615 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.4001 Generator loss: 0.8338 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.4142 Generator loss: 0.7978 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.3896 Generator loss: 0.8289 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.3671 Generator loss: 0.8244
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [12:05<08:52, 5.12batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.4255 Generator loss: 0.7892 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.4139 Generator loss: 0.7104 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.4162 Generator loss: 0.7807 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.3979 Generator loss: 0.7305 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.3950 Generator loss: 0.7523 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.3924 Generator loss: 0.8233 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3732 Generator loss: 0.7731 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.4031 Generator loss: 0.7631 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.3822 Generator loss: 0.7572 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.4059 Generator loss: 0.7868
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [12:24<08:27, 5.19batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.4244 Generator loss: 0.7533 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.3974 Generator loss: 0.8491 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.4009 Generator loss: 0.7756 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.4384 Generator loss: 0.7793 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.3986 Generator loss: 0.7820 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.4460 Generator loss: 0.8555 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.4026 Generator loss: 0.7824 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.4029 Generator loss: 0.7915 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.4051 Generator loss: 0.7394 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.4440 Generator loss: 0.7596
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [12:44<08:11, 5.15batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.4007 Generator loss: 0.7709 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.3823 Generator loss: 0.8244 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.3917 Generator loss: 0.7001 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.3919 Generator loss: 0.7969 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.3715 Generator loss: 0.7882 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.3968 Generator loss: 0.8211 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.4114 Generator loss: 0.7933 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.3743 Generator loss: 0.7474 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.4123 Generator loss: 0.8355 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.3870 Generator loss: 0.7429
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [13:05<08:10, 4.96batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.3837 Generator loss: 0.7842 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.4119 Generator loss: 0.7449 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.3913 Generator loss: 0.7616 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.4079 Generator loss: 0.7377 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.3967 Generator loss: 0.7805 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.4073 Generator loss: 0.7794 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.4223 Generator loss: 0.7580 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.4027 Generator loss: 0.8335 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.3979 Generator loss: 0.7960 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.3721 Generator loss: 0.8037
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [13:25<07:48, 4.97batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.3925 Generator loss: 0.7828 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.4204 Generator loss: 0.7747 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.3860 Generator loss: 0.7499 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.3860 Generator loss: 0.7214 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.3859 Generator loss: 0.7694 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.4085 Generator loss: 0.7902 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.3937 Generator loss: 0.7359 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.3750 Generator loss: 0.8163 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.3718 Generator loss: 0.8215 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.3798 Generator loss: 0.7194
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [13:46<07:33, 4.92batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.3941 Generator loss: 0.7721 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.3789 Generator loss: 0.7745 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.4342 Generator loss: 0.7486 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.3958 Generator loss: 0.8036 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.4564 Generator loss: 0.7446 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.3582 Generator loss: 0.8181 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.4044 Generator loss: 0.7909 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.4023 Generator loss: 0.7795 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.3836 Generator loss: 0.7889 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.3843 Generator loss: 0.7666
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.3968 Generator loss: 0.7284 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.3963 Generator loss: 0.7582 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.4077 Generator loss: 0.7939 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.3907 Generator loss: 0.8004 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.4178 Generator loss: 0.7540 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.3791 Generator loss: 0.7478 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.4185 Generator loss: 0.7341 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.3811 Generator loss: 0.7685 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.4102 Generator loss: 0.7443 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.4152 Generator loss: 0.7517
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.3974 Generator loss: 0.7778 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.3839 Generator loss: 0.7125 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3899 Generator loss: 0.7614 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.4024 Generator loss: 0.7288 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.4070 Generator loss: 0.7861 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.3760 Generator loss: 0.8123 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.3879 Generator loss: 0.7557 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.3711 Generator loss: 0.8140 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.3969 Generator loss: 0.7589 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.3892 Generator loss: 0.7397
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Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.4133 Generator loss: 0.7757 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.3962 Generator loss: 0.7787 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.3941 Generator loss: 0.8004 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.3864 Generator loss: 0.7903 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.4071 Generator loss: 0.8272 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.4173 Generator loss: 0.7603 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.3724 Generator loss: 0.7837 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.4088 Generator loss: 0.7913 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.3870 Generator loss: 0.8554 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.3882 Generator loss: 0.8385
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Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.4215 Generator loss: 0.7485 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.4002 Generator loss: 0.7918 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.3879 Generator loss: 0.7790 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.4189 Generator loss: 0.7220 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.4121 Generator loss: 0.7575 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.3884 Generator loss: 0.7740 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.4071 Generator loss: 0.7455 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.3942 Generator loss: 0.7465 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.4002 Generator loss: 0.7909 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.3956 Generator loss: 0.7694
Batches: 74%|█████████████████████████████████████████████████████▍ | 4700/6331 [15:57<05:55, 4.59batch/s]
Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.3998 Generator loss: 0.8007 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3811 Generator loss: 0.8039 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3961 Generator loss: 0.7555 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.3972 Generator loss: 0.7439 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.3971 Generator loss: 0.8426 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.3813 Generator loss: 0.7551 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.3923 Generator loss: 0.8171 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.3987 Generator loss: 0.7509 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.3963 Generator loss: 0.7867 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.4030 Generator loss: 0.7787
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [16:18<05:28, 4.67batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.3874 Generator loss: 0.8089 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.3835 Generator loss: 0.7662 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.3825 Generator loss: 0.8019 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.3870 Generator loss: 0.8171 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.3807 Generator loss: 0.8007 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.3937 Generator loss: 0.7844 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3866 Generator loss: 0.7973 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.3965 Generator loss: 0.7997 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.3882 Generator loss: 0.8070 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.3959 Generator loss: 0.8211
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [16:39<05:06, 4.67batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.3907 Generator loss: 0.8016 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.3829 Generator loss: 0.8039 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.3787 Generator loss: 0.7989 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.3861 Generator loss: 0.8177 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.3841 Generator loss: 0.7636 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.3760 Generator loss: 0.7878 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.3828 Generator loss: 0.7914 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.3965 Generator loss: 0.7389 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.3883 Generator loss: 0.7851 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.3902 Generator loss: 0.8074
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [17:03<04:52, 4.55batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.3883 Generator loss: 0.7730 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.4107 Generator loss: 0.7615 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.3915 Generator loss: 0.7454 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.4138 Generator loss: 0.7816 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.3794 Generator loss: 0.7522 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.3870 Generator loss: 0.7965 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.3929 Generator loss: 0.7610 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.3888 Generator loss: 0.7757 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.3945 Generator loss: 0.7808 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.4084 Generator loss: 0.7591
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [17:22<04:22, 4.70batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.3854 Generator loss: 0.7817 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.3903 Generator loss: 0.7695 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.3863 Generator loss: 0.7711 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.4058 Generator loss: 0.7507 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.3962 Generator loss: 0.7837 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3878 Generator loss: 0.7951 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.3930 Generator loss: 0.7736 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.3961 Generator loss: 0.7712 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.3921 Generator loss: 0.7863 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.3905 Generator loss: 0.7875
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [17:41<03:51, 4.88batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.3777 Generator loss: 0.7989 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.3821 Generator loss: 0.7871 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.3950 Generator loss: 0.7647 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.3822 Generator loss: 0.8026 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.3892 Generator loss: 0.7937 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.3958 Generator loss: 0.7635 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.3798 Generator loss: 0.7707 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.3955 Generator loss: 0.7861 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.3802 Generator loss: 0.8070 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.3776 Generator loss: 0.7706
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [17:57<03:17, 5.23batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.4037 Generator loss: 0.7685 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3853 Generator loss: 0.7527 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3860 Generator loss: 0.8130 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.4001 Generator loss: 0.7838 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.3847 Generator loss: 0.7898 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.3893 Generator loss: 0.7945 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3902 Generator loss: 0.7774 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.3837 Generator loss: 0.8109 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3734 Generator loss: 0.7936 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.3796 Generator loss: 0.7888
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [18:10<02:41, 5.77batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3824 Generator loss: 0.8192 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3905 Generator loss: 0.7902 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3948 Generator loss: 0.7628 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3893 Generator loss: 0.8022 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.3920 Generator loss: 0.7781 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3792 Generator loss: 0.7773 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3873 Generator loss: 0.8259 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.3871 Generator loss: 0.7731 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.3717 Generator loss: 0.7917 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.3941 Generator loss: 0.8148
Batches: 87%|██████████████████████████████████████████████████████████████▌ | 5500/6331 [18:24<02:16, 6.08batch/s]
Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.3813 Generator loss: 0.7869 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3852 Generator loss: 0.7928 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3876 Generator loss: 0.7808 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.3779 Generator loss: 0.7988 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3991 Generator loss: 0.7616 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.3875 Generator loss: 0.7890 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3889 Generator loss: 0.8362 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.3828 Generator loss: 0.7801 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.3950 Generator loss: 0.7731 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.3888 Generator loss: 0.7891
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Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.3846 Generator loss: 0.8077 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3837 Generator loss: 0.7958 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3801 Generator loss: 0.7630 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3787 Generator loss: 0.8034 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.3898 Generator loss: 0.7507 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3778 Generator loss: 0.7719 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3864 Generator loss: 0.7642 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.3820 Generator loss: 0.7624 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.3741 Generator loss: 0.7866 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3939 Generator loss: 0.7712
Batches: 90%|████████████████████████████████████████████████████████████████▊ | 5700/6331 [18:53<01:37, 6.50batch/s]
Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3876 Generator loss: 0.7750 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.3921 Generator loss: 0.7764 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.3941 Generator loss: 0.7569 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.3794 Generator loss: 0.7902 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.3847 Generator loss: 0.7783 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.3728 Generator loss: 0.7991 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.3792 Generator loss: 0.7831 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.3829 Generator loss: 0.7972 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3861 Generator loss: 0.7838 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.3900 Generator loss: 0.7754
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Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.3845 Generator loss: 0.7881 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.4016 Generator loss: 0.7965 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.3738 Generator loss: 0.7893 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.3771 Generator loss: 0.8358 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.3823 Generator loss: 0.8090 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.3766 Generator loss: 0.7818 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3854 Generator loss: 0.7814 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.3853 Generator loss: 0.7924 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.3893 Generator loss: 0.7769 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3722 Generator loss: 0.8090
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3890 Generator loss: 0.7774 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3804 Generator loss: 0.7872 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3934 Generator loss: 0.8175 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3811 Generator loss: 0.7973 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.3854 Generator loss: 0.7754 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.3958 Generator loss: 0.7982 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3913 Generator loss: 0.7789 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.3864 Generator loss: 0.7614 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.3873 Generator loss: 0.7890 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3866 Generator loss: 0.8133
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.3938 Generator loss: 0.7680 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3823 Generator loss: 0.7899 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3807 Generator loss: 0.7815 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.3940 Generator loss: 0.7829 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3884 Generator loss: 0.7680 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.3953 Generator loss: 0.7765 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.3813 Generator loss: 0.7832 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.3936 Generator loss: 0.7680 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.3968 Generator loss: 0.7422 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3861 Generator loss: 0.7908
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.3862 Generator loss: 0.7712 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.3866 Generator loss: 0.7842 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3841 Generator loss: 0.7906 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.3885 Generator loss: 0.8002 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.3833 Generator loss: 0.7859 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.3775 Generator loss: 0.7886 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.3811 Generator loss: 0.7816 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.3867 Generator loss: 0.7958 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3896 Generator loss: 0.7824 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3828 Generator loss: 0.8029
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [20:02<00:18, 7.09batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.3912 Generator loss: 0.7896 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3829 Generator loss: 0.7804 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3846 Generator loss: 0.7581 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3795 Generator loss: 0.8195 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.3891 Generator loss: 0.7847 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3864 Generator loss: 0.7739 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3843 Generator loss: 0.8050 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3852 Generator loss: 0.7959 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3824 Generator loss: 0.7909 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3853 Generator loss: 0.7959
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [20:16<00:04, 7.14batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.3794 Generator loss: 0.7933 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.3674 Generator loss: 0.7927 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3816 Generator loss: 0.8045
Epochs: 100%|█████████████████████████████████████████████████████████████████████████████| 1/1 [20:20<00:00, 1220.43s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.002
beta1 = 0.3
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
Epochs: 0%| | 0/1 [00:00<?, ?epoch/s] Batches: 0%| | 0/6331 [00:00<?, ?batch/s]
Epoch 0/1... Batch 10/6331... Discriminator loss: 3.9754 Generator loss: 0.1650 Epoch 0/1... Batch 20/6331... Discriminator loss: 2.0891 Generator loss: 0.2722 Epoch 0/1... Batch 30/6331... Discriminator loss: 1.5292 Generator loss: 1.1602 Epoch 0/1... Batch 40/6331... Discriminator loss: 1.3910 Generator loss: 1.4078 Epoch 0/1... Batch 50/6331... Discriminator loss: 1.5541 Generator loss: 0.6097 Epoch 0/1... Batch 60/6331... Discriminator loss: 3.4607 Generator loss: 2.9490 Epoch 0/1... Batch 70/6331... Discriminator loss: 1.4156 Generator loss: 1.1056 Epoch 0/1... Batch 80/6331... Discriminator loss: 1.3131 Generator loss: 1.4627 Epoch 0/1... Batch 90/6331... Discriminator loss: 1.3870 Generator loss: 0.8783 Epoch 0/1... Batch 100/6331... Discriminator loss: 1.4284 Generator loss: 0.5692
Batches: 2%|█▏ | 100/6331 [00:13<14:18, 7.26batch/s]
Epoch 0/1... Batch 110/6331... Discriminator loss: 2.3961 Generator loss: 0.3325 Epoch 0/1... Batch 120/6331... Discriminator loss: 1.6608 Generator loss: 0.6194 Epoch 0/1... Batch 130/6331... Discriminator loss: 1.7591 Generator loss: 0.6958 Epoch 0/1... Batch 140/6331... Discriminator loss: 1.5826 Generator loss: 0.5292 Epoch 0/1... Batch 150/6331... Discriminator loss: 1.5203 Generator loss: 0.6302 Epoch 0/1... Batch 160/6331... Discriminator loss: 1.6977 Generator loss: 0.5293 Epoch 0/1... Batch 170/6331... Discriminator loss: 2.3793 Generator loss: 0.8690 Epoch 0/1... Batch 180/6331... Discriminator loss: 1.4595 Generator loss: 0.5302 Epoch 0/1... Batch 190/6331... Discriminator loss: 2.3990 Generator loss: 0.2592 Epoch 0/1... Batch 200/6331... Discriminator loss: 1.4603 Generator loss: 0.8557
Batches: 3%|██▎ | 200/6331 [00:27<13:56, 7.33batch/s]
Epoch 0/1... Batch 210/6331... Discriminator loss: 1.6008 Generator loss: 0.7085 Epoch 0/1... Batch 220/6331... Discriminator loss: 1.5260 Generator loss: 0.7477 Epoch 0/1... Batch 230/6331... Discriminator loss: 1.4714 Generator loss: 0.8830 Epoch 0/1... Batch 240/6331... Discriminator loss: 1.5238 Generator loss: 0.6388 Epoch 0/1... Batch 250/6331... Discriminator loss: 1.5442 Generator loss: 0.6673 Epoch 0/1... Batch 260/6331... Discriminator loss: 1.7661 Generator loss: 0.5013 Epoch 0/1... Batch 270/6331... Discriminator loss: 1.4713 Generator loss: 0.9840 Epoch 0/1... Batch 280/6331... Discriminator loss: 1.4686 Generator loss: 0.6756 Epoch 0/1... Batch 290/6331... Discriminator loss: 1.6939 Generator loss: 0.6037 Epoch 0/1... Batch 300/6331... Discriminator loss: 1.3958 Generator loss: 0.8836
Batches: 5%|███▍ | 300/6331 [00:41<14:01, 7.16batch/s]
Epoch 0/1... Batch 310/6331... Discriminator loss: 1.5609 Generator loss: 0.5396 Epoch 0/1... Batch 320/6331... Discriminator loss: 1.4529 Generator loss: 0.6442 Epoch 0/1... Batch 330/6331... Discriminator loss: 1.6195 Generator loss: 0.7108 Epoch 0/1... Batch 340/6331... Discriminator loss: 1.4886 Generator loss: 0.7618 Epoch 0/1... Batch 350/6331... Discriminator loss: 1.5131 Generator loss: 0.6900 Epoch 0/1... Batch 360/6331... Discriminator loss: 1.4492 Generator loss: 0.6242 Epoch 0/1... Batch 370/6331... Discriminator loss: 1.4766 Generator loss: 0.7120 Epoch 0/1... Batch 380/6331... Discriminator loss: 1.5052 Generator loss: 0.7291 Epoch 0/1... Batch 390/6331... Discriminator loss: 1.4652 Generator loss: 0.7663 Epoch 0/1... Batch 400/6331... Discriminator loss: 1.4861 Generator loss: 0.7472
Batches: 6%|████▌ | 400/6331 [00:57<14:17, 6.92batch/s]
Epoch 0/1... Batch 410/6331... Discriminator loss: 1.5733 Generator loss: 0.6276 Epoch 0/1... Batch 420/6331... Discriminator loss: 1.6487 Generator loss: 0.5782 Epoch 0/1... Batch 430/6331... Discriminator loss: 1.4759 Generator loss: 0.6065 Epoch 0/1... Batch 440/6331... Discriminator loss: 1.4839 Generator loss: 0.6674 Epoch 0/1... Batch 450/6331... Discriminator loss: 1.5895 Generator loss: 0.7082 Epoch 0/1... Batch 460/6331... Discriminator loss: 1.5227 Generator loss: 0.7739 Epoch 0/1... Batch 470/6331... Discriminator loss: 1.6212 Generator loss: 0.4643 Epoch 0/1... Batch 480/6331... Discriminator loss: 1.4399 Generator loss: 1.0099 Epoch 0/1... Batch 490/6331... Discriminator loss: 1.5532 Generator loss: 0.6102 Epoch 0/1... Batch 500/6331... Discriminator loss: 1.4458 Generator loss: 0.7662
Batches: 8%|█████▊ | 500/6331 [01:11<13:53, 6.99batch/s]
Epoch 0/1... Batch 510/6331... Discriminator loss: 1.4579 Generator loss: 0.8043 Epoch 0/1... Batch 520/6331... Discriminator loss: 1.6286 Generator loss: 0.8256 Epoch 0/1... Batch 530/6331... Discriminator loss: 1.5472 Generator loss: 0.5692 Epoch 0/1... Batch 540/6331... Discriminator loss: 1.6379 Generator loss: 0.5994 Epoch 0/1... Batch 550/6331... Discriminator loss: 1.4308 Generator loss: 0.7738 Epoch 0/1... Batch 560/6331... Discriminator loss: 1.6003 Generator loss: 0.4447 Epoch 0/1... Batch 570/6331... Discriminator loss: 1.5651 Generator loss: 0.5710 Epoch 0/1... Batch 580/6331... Discriminator loss: 1.4256 Generator loss: 0.8987 Epoch 0/1... Batch 590/6331... Discriminator loss: 1.6066 Generator loss: 0.5654 Epoch 0/1... Batch 600/6331... Discriminator loss: 1.4569 Generator loss: 0.8322
Batches: 9%|██████▉ | 600/6331 [01:26<13:55, 6.86batch/s]
Epoch 0/1... Batch 610/6331... Discriminator loss: 1.4783 Generator loss: 0.7019 Epoch 0/1... Batch 620/6331... Discriminator loss: 1.5133 Generator loss: 0.7840 Epoch 0/1... Batch 630/6331... Discriminator loss: 1.5400 Generator loss: 0.7313 Epoch 0/1... Batch 640/6331... Discriminator loss: 1.5880 Generator loss: 0.5531 Epoch 0/1... Batch 650/6331... Discriminator loss: 1.5843 Generator loss: 0.6979 Epoch 0/1... Batch 660/6331... Discriminator loss: 1.5723 Generator loss: 0.6880 Epoch 0/1... Batch 670/6331... Discriminator loss: 1.5365 Generator loss: 0.8244 Epoch 0/1... Batch 680/6331... Discriminator loss: 1.5619 Generator loss: 0.6707 Epoch 0/1... Batch 690/6331... Discriminator loss: 1.4949 Generator loss: 0.9527 Epoch 0/1... Batch 700/6331... Discriminator loss: 1.4655 Generator loss: 0.6108
Batches: 11%|████████ | 700/6331 [01:40<13:31, 6.94batch/s]
Epoch 0/1... Batch 710/6331... Discriminator loss: 1.4240 Generator loss: 0.6809 Epoch 0/1... Batch 720/6331... Discriminator loss: 1.3980 Generator loss: 0.8277 Epoch 0/1... Batch 730/6331... Discriminator loss: 1.5432 Generator loss: 0.5988 Epoch 0/1... Batch 740/6331... Discriminator loss: 1.4805 Generator loss: 0.6282 Epoch 0/1... Batch 750/6331... Discriminator loss: 1.4803 Generator loss: 0.7744 Epoch 0/1... Batch 760/6331... Discriminator loss: 1.4967 Generator loss: 0.7478 Epoch 0/1... Batch 770/6331... Discriminator loss: 1.4164 Generator loss: 0.8177 Epoch 0/1... Batch 780/6331... Discriminator loss: 1.4593 Generator loss: 0.6113 Epoch 0/1... Batch 790/6331... Discriminator loss: 1.4564 Generator loss: 0.9003 Epoch 0/1... Batch 800/6331... Discriminator loss: 1.4095 Generator loss: 0.7620
Batches: 13%|█████████▏ | 800/6331 [01:56<13:46, 6.70batch/s]
Epoch 0/1... Batch 810/6331... Discriminator loss: 1.4888 Generator loss: 0.8335 Epoch 0/1... Batch 820/6331... Discriminator loss: 1.4658 Generator loss: 0.8376 Epoch 0/1... Batch 830/6331... Discriminator loss: 1.5773 Generator loss: 0.6871 Epoch 0/1... Batch 840/6331... Discriminator loss: 1.4586 Generator loss: 0.7980 Epoch 0/1... Batch 850/6331... Discriminator loss: 1.4445 Generator loss: 0.7880 Epoch 0/1... Batch 860/6331... Discriminator loss: 1.4176 Generator loss: 0.8421 Epoch 0/1... Batch 870/6331... Discriminator loss: 1.4576 Generator loss: 0.6995 Epoch 0/1... Batch 880/6331... Discriminator loss: 1.4885 Generator loss: 1.0701 Epoch 0/1... Batch 890/6331... Discriminator loss: 1.3957 Generator loss: 0.6886 Epoch 0/1... Batch 900/6331... Discriminator loss: 1.4388 Generator loss: 0.6443
Batches: 14%|██████████▍ | 900/6331 [02:11<13:20, 6.79batch/s]
Epoch 0/1... Batch 910/6331... Discriminator loss: 1.4323 Generator loss: 0.8994 Epoch 0/1... Batch 920/6331... Discriminator loss: 1.5955 Generator loss: 0.6463 Epoch 0/1... Batch 930/6331... Discriminator loss: 1.4374 Generator loss: 0.7459 Epoch 0/1... Batch 940/6331... Discriminator loss: 1.4850 Generator loss: 0.6658 Epoch 0/1... Batch 950/6331... Discriminator loss: 1.4522 Generator loss: 0.7066 Epoch 0/1... Batch 960/6331... Discriminator loss: 1.4497 Generator loss: 0.7206 Epoch 0/1... Batch 970/6331... Discriminator loss: 1.4390 Generator loss: 0.8370 Epoch 0/1... Batch 980/6331... Discriminator loss: 1.4078 Generator loss: 0.7323 Epoch 0/1... Batch 990/6331... Discriminator loss: 1.4531 Generator loss: 0.7504 Epoch 0/1... Batch 1000/6331... Discriminator loss: 1.4498 Generator loss: 0.6883
Batches: 16%|███████████▎ | 1000/6331 [02:26<13:20, 6.66batch/s]
Epoch 0/1... Batch 1010/6331... Discriminator loss: 1.4094 Generator loss: 0.7986 Epoch 0/1... Batch 1020/6331... Discriminator loss: 1.4616 Generator loss: 0.8185 Epoch 0/1... Batch 1030/6331... Discriminator loss: 1.4508 Generator loss: 0.8719 Epoch 0/1... Batch 1040/6331... Discriminator loss: 1.4524 Generator loss: 0.6524 Epoch 0/1... Batch 1050/6331... Discriminator loss: 1.5423 Generator loss: 0.6138 Epoch 0/1... Batch 1060/6331... Discriminator loss: 1.4089 Generator loss: 0.7123 Epoch 0/1... Batch 1070/6331... Discriminator loss: 1.4552 Generator loss: 0.8124 Epoch 0/1... Batch 1080/6331... Discriminator loss: 1.4585 Generator loss: 0.8063 Epoch 0/1... Batch 1090/6331... Discriminator loss: 1.4089 Generator loss: 1.0119 Epoch 0/1... Batch 1100/6331... Discriminator loss: 1.4624 Generator loss: 0.6566
Batches: 17%|████████████▌ | 1100/6331 [02:41<13:02, 6.68batch/s]
Epoch 0/1... Batch 1110/6331... Discriminator loss: 1.5121 Generator loss: 0.7988 Epoch 0/1... Batch 1120/6331... Discriminator loss: 1.4966 Generator loss: 0.6060 Epoch 0/1... Batch 1130/6331... Discriminator loss: 1.4115 Generator loss: 0.7373 Epoch 0/1... Batch 1140/6331... Discriminator loss: 1.4805 Generator loss: 0.7679 Epoch 0/1... Batch 1150/6331... Discriminator loss: 1.4450 Generator loss: 0.6774 Epoch 0/1... Batch 1160/6331... Discriminator loss: 1.4470 Generator loss: 0.7149 Epoch 0/1... Batch 1170/6331... Discriminator loss: 1.4187 Generator loss: 0.6977 Epoch 0/1... Batch 1180/6331... Discriminator loss: 1.4831 Generator loss: 0.8607 Epoch 0/1... Batch 1190/6331... Discriminator loss: 1.3736 Generator loss: 0.7208 Epoch 0/1... Batch 1200/6331... Discriminator loss: 1.4028 Generator loss: 0.8438
Batches: 19%|█████████████▋ | 1200/6331 [02:55<12:34, 6.80batch/s]
Epoch 0/1... Batch 1210/6331... Discriminator loss: 1.4382 Generator loss: 0.8536 Epoch 0/1... Batch 1220/6331... Discriminator loss: 1.4058 Generator loss: 0.8088 Epoch 0/1... Batch 1230/6331... Discriminator loss: 1.4210 Generator loss: 0.7770 Epoch 0/1... Batch 1240/6331... Discriminator loss: 1.4444 Generator loss: 0.6070 Epoch 0/1... Batch 1250/6331... Discriminator loss: 1.4306 Generator loss: 0.6926 Epoch 0/1... Batch 1260/6331... Discriminator loss: 1.4287 Generator loss: 0.8467 Epoch 0/1... Batch 1270/6331... Discriminator loss: 1.5123 Generator loss: 0.5745 Epoch 0/1... Batch 1280/6331... Discriminator loss: 1.4634 Generator loss: 0.7299 Epoch 0/1... Batch 1290/6331... Discriminator loss: 1.5104 Generator loss: 0.6694 Epoch 0/1... Batch 1300/6331... Discriminator loss: 1.4335 Generator loss: 0.8640
Batches: 21%|██████████████▊ | 1300/6331 [03:09<12:04, 6.94batch/s]
Epoch 0/1... Batch 1310/6331... Discriminator loss: 1.4249 Generator loss: 0.6445 Epoch 0/1... Batch 1320/6331... Discriminator loss: 1.3841 Generator loss: 0.7935 Epoch 0/1... Batch 1330/6331... Discriminator loss: 1.4369 Generator loss: 0.8937 Epoch 0/1... Batch 1340/6331... Discriminator loss: 1.4436 Generator loss: 0.7032 Epoch 0/1... Batch 1350/6331... Discriminator loss: 1.4549 Generator loss: 0.6544 Epoch 0/1... Batch 1360/6331... Discriminator loss: 1.4268 Generator loss: 0.6293 Epoch 0/1... Batch 1370/6331... Discriminator loss: 1.4258 Generator loss: 0.6665 Epoch 0/1... Batch 1380/6331... Discriminator loss: 1.4558 Generator loss: 0.7253 Epoch 0/1... Batch 1390/6331... Discriminator loss: 1.4888 Generator loss: 0.5841 Epoch 0/1... Batch 1400/6331... Discriminator loss: 1.4582 Generator loss: 0.7633
Batches: 22%|███████████████▉ | 1400/6331 [03:23<11:51, 6.93batch/s]
Epoch 0/1... Batch 1410/6331... Discriminator loss: 1.4097 Generator loss: 0.7344 Epoch 0/1... Batch 1420/6331... Discriminator loss: 1.4499 Generator loss: 0.7576 Epoch 0/1... Batch 1430/6331... Discriminator loss: 1.3975 Generator loss: 0.7852 Epoch 0/1... Batch 1440/6331... Discriminator loss: 1.4814 Generator loss: 0.8245 Epoch 0/1... Batch 1450/6331... Discriminator loss: 1.4057 Generator loss: 0.7270 Epoch 0/1... Batch 1460/6331... Discriminator loss: 1.4063 Generator loss: 0.9962 Epoch 0/1... Batch 1470/6331... Discriminator loss: 1.4296 Generator loss: 0.7834 Epoch 0/1... Batch 1480/6331... Discriminator loss: 1.4466 Generator loss: 0.7031 Epoch 0/1... Batch 1490/6331... Discriminator loss: 1.4082 Generator loss: 0.7299 Epoch 0/1... Batch 1500/6331... Discriminator loss: 1.4575 Generator loss: 0.7664
Batches: 24%|█████████████████ | 1500/6331 [03:37<11:26, 7.04batch/s]
Epoch 0/1... Batch 1510/6331... Discriminator loss: 1.4230 Generator loss: 0.7251 Epoch 0/1... Batch 1520/6331... Discriminator loss: 1.4347 Generator loss: 0.7412 Epoch 0/1... Batch 1530/6331... Discriminator loss: 1.4359 Generator loss: 0.7128 Epoch 0/1... Batch 1540/6331... Discriminator loss: 1.4319 Generator loss: 0.8533 Epoch 0/1... Batch 1550/6331... Discriminator loss: 1.4524 Generator loss: 0.9416 Epoch 0/1... Batch 1560/6331... Discriminator loss: 1.4229 Generator loss: 0.7653 Epoch 0/1... Batch 1570/6331... Discriminator loss: 1.3923 Generator loss: 0.8002 Epoch 0/1... Batch 1580/6331... Discriminator loss: 1.4069 Generator loss: 0.8185 Epoch 0/1... Batch 1590/6331... Discriminator loss: 1.4054 Generator loss: 0.7560 Epoch 0/1... Batch 1600/6331... Discriminator loss: 1.4513 Generator loss: 0.9158
Batches: 25%|██████████████████▏ | 1600/6331 [03:51<11:02, 7.14batch/s]
Epoch 0/1... Batch 1610/6331... Discriminator loss: 1.4783 Generator loss: 0.8811 Epoch 0/1... Batch 1620/6331... Discriminator loss: 1.3983 Generator loss: 0.8104 Epoch 0/1... Batch 1630/6331... Discriminator loss: 1.4260 Generator loss: 0.7004 Epoch 0/1... Batch 1640/6331... Discriminator loss: 1.4190 Generator loss: 0.7969 Epoch 0/1... Batch 1650/6331... Discriminator loss: 1.4515 Generator loss: 0.7705 Epoch 0/1... Batch 1660/6331... Discriminator loss: 1.4431 Generator loss: 0.8116 Epoch 0/1... Batch 1670/6331... Discriminator loss: 1.4537 Generator loss: 0.6571 Epoch 0/1... Batch 1680/6331... Discriminator loss: 1.4300 Generator loss: 0.7041 Epoch 0/1... Batch 1690/6331... Discriminator loss: 1.4430 Generator loss: 0.8948 Epoch 0/1... Batch 1700/6331... Discriminator loss: 1.4242 Generator loss: 0.8495
Batches: 27%|███████████████████▎ | 1700/6331 [04:05<10:55, 7.07batch/s]
Epoch 0/1... Batch 1710/6331... Discriminator loss: 1.4100 Generator loss: 0.7428 Epoch 0/1... Batch 1720/6331... Discriminator loss: 1.4332 Generator loss: 0.7562 Epoch 0/1... Batch 1730/6331... Discriminator loss: 1.4754 Generator loss: 0.8768 Epoch 0/1... Batch 1740/6331... Discriminator loss: 1.4122 Generator loss: 0.8790 Epoch 0/1... Batch 1750/6331... Discriminator loss: 1.4484 Generator loss: 0.7293 Epoch 0/1... Batch 1760/6331... Discriminator loss: 1.4623 Generator loss: 0.7919 Epoch 0/1... Batch 1770/6331... Discriminator loss: 1.4093 Generator loss: 0.8492 Epoch 0/1... Batch 1780/6331... Discriminator loss: 1.4861 Generator loss: 0.8567 Epoch 0/1... Batch 1790/6331... Discriminator loss: 1.4037 Generator loss: 0.6832 Epoch 0/1... Batch 1800/6331... Discriminator loss: 1.4026 Generator loss: 0.7537
Batches: 28%|████████████████████▍ | 1800/6331 [04:18<10:31, 7.17batch/s]
Epoch 0/1... Batch 1810/6331... Discriminator loss: 1.4105 Generator loss: 0.7725 Epoch 0/1... Batch 1820/6331... Discriminator loss: 1.3738 Generator loss: 0.7116 Epoch 0/1... Batch 1830/6331... Discriminator loss: 1.4180 Generator loss: 0.8286 Epoch 0/1... Batch 1840/6331... Discriminator loss: 1.3962 Generator loss: 0.8027 Epoch 0/1... Batch 1850/6331... Discriminator loss: 1.3875 Generator loss: 0.7652 Epoch 0/1... Batch 1860/6331... Discriminator loss: 1.3963 Generator loss: 0.8240 Epoch 0/1... Batch 1870/6331... Discriminator loss: 1.4027 Generator loss: 0.8087 Epoch 0/1... Batch 1880/6331... Discriminator loss: 1.4430 Generator loss: 0.6899 Epoch 0/1... Batch 1890/6331... Discriminator loss: 1.4244 Generator loss: 0.7614 Epoch 0/1... Batch 1900/6331... Discriminator loss: 1.4330 Generator loss: 0.7896
Batches: 30%|█████████████████████▌ | 1900/6331 [04:33<10:19, 7.15batch/s]
Epoch 0/1... Batch 1910/6331... Discriminator loss: 1.4143 Generator loss: 0.9446 Epoch 0/1... Batch 1920/6331... Discriminator loss: 1.3718 Generator loss: 0.7614 Epoch 0/1... Batch 1930/6331... Discriminator loss: 1.4173 Generator loss: 0.7802 Epoch 0/1... Batch 1940/6331... Discriminator loss: 1.4181 Generator loss: 0.7063 Epoch 0/1... Batch 1950/6331... Discriminator loss: 1.3923 Generator loss: 0.7329 Epoch 0/1... Batch 1960/6331... Discriminator loss: 1.4750 Generator loss: 0.8093 Epoch 0/1... Batch 1970/6331... Discriminator loss: 1.4082 Generator loss: 0.7383 Epoch 0/1... Batch 1980/6331... Discriminator loss: 1.3932 Generator loss: 0.7144 Epoch 0/1... Batch 1990/6331... Discriminator loss: 1.4983 Generator loss: 0.5704 Epoch 0/1... Batch 2000/6331... Discriminator loss: 1.4322 Generator loss: 0.8317
Batches: 32%|██████████████████████▋ | 2000/6331 [04:46<10:00, 7.21batch/s]
Epoch 0/1... Batch 2010/6331... Discriminator loss: 1.5120 Generator loss: 0.7565 Epoch 0/1... Batch 2020/6331... Discriminator loss: 1.4621 Generator loss: 0.8208 Epoch 0/1... Batch 2030/6331... Discriminator loss: 1.4753 Generator loss: 0.6436 Epoch 0/1... Batch 2040/6331... Discriminator loss: 1.4390 Generator loss: 0.7907 Epoch 0/1... Batch 2050/6331... Discriminator loss: 1.4415 Generator loss: 0.8825 Epoch 0/1... Batch 2060/6331... Discriminator loss: 1.4135 Generator loss: 0.6715 Epoch 0/1... Batch 2070/6331... Discriminator loss: 1.4380 Generator loss: 0.7932 Epoch 0/1... Batch 2080/6331... Discriminator loss: 1.4017 Generator loss: 0.7528 Epoch 0/1... Batch 2090/6331... Discriminator loss: 1.4527 Generator loss: 0.7330 Epoch 0/1... Batch 2100/6331... Discriminator loss: 1.4339 Generator loss: 0.7691
Batches: 33%|███████████████████████▉ | 2100/6331 [04:59<09:37, 7.32batch/s]
Epoch 0/1... Batch 2110/6331... Discriminator loss: 1.3758 Generator loss: 0.7486 Epoch 0/1... Batch 2120/6331... Discriminator loss: 1.4308 Generator loss: 0.7085 Epoch 0/1... Batch 2130/6331... Discriminator loss: 1.4219 Generator loss: 0.7218 Epoch 0/1... Batch 2140/6331... Discriminator loss: 1.3756 Generator loss: 0.7116 Epoch 0/1... Batch 2150/6331... Discriminator loss: 1.4807 Generator loss: 0.6674 Epoch 0/1... Batch 2160/6331... Discriminator loss: 1.4009 Generator loss: 0.8015 Epoch 0/1... Batch 2170/6331... Discriminator loss: 1.4344 Generator loss: 0.6958 Epoch 0/1... Batch 2180/6331... Discriminator loss: 1.3914 Generator loss: 0.7613 Epoch 0/1... Batch 2190/6331... Discriminator loss: 1.3813 Generator loss: 0.8259 Epoch 0/1... Batch 2200/6331... Discriminator loss: 1.4273 Generator loss: 0.7899
Batches: 35%|█████████████████████████ | 2200/6331 [05:13<09:28, 7.27batch/s]
Epoch 0/1... Batch 2210/6331... Discriminator loss: 1.4854 Generator loss: 0.7197 Epoch 0/1... Batch 2220/6331... Discriminator loss: 1.3913 Generator loss: 0.7291 Epoch 0/1... Batch 2230/6331... Discriminator loss: 1.3755 Generator loss: 0.7964 Epoch 0/1... Batch 2240/6331... Discriminator loss: 1.4183 Generator loss: 0.7795 Epoch 0/1... Batch 2250/6331... Discriminator loss: 1.3839 Generator loss: 0.8197 Epoch 0/1... Batch 2260/6331... Discriminator loss: 1.4514 Generator loss: 0.7093 Epoch 0/1... Batch 2270/6331... Discriminator loss: 1.4181 Generator loss: 0.7979 Epoch 0/1... Batch 2280/6331... Discriminator loss: 1.4139 Generator loss: 0.7622 Epoch 0/1... Batch 2290/6331... Discriminator loss: 1.3731 Generator loss: 0.8642 Epoch 0/1... Batch 2300/6331... Discriminator loss: 1.4114 Generator loss: 0.6959
Batches: 36%|██████████████████████████▏ | 2300/6331 [05:27<09:15, 7.26batch/s]
Epoch 0/1... Batch 2310/6331... Discriminator loss: 1.4375 Generator loss: 0.7839 Epoch 0/1... Batch 2320/6331... Discriminator loss: 1.3838 Generator loss: 0.8147 Epoch 0/1... Batch 2330/6331... Discriminator loss: 1.4355 Generator loss: 0.7948 Epoch 0/1... Batch 2340/6331... Discriminator loss: 1.4107 Generator loss: 0.7615 Epoch 0/1... Batch 2350/6331... Discriminator loss: 1.4661 Generator loss: 0.5680 Epoch 0/1... Batch 2360/6331... Discriminator loss: 1.3978 Generator loss: 0.7313 Epoch 0/1... Batch 2370/6331... Discriminator loss: 1.5036 Generator loss: 0.6057 Epoch 0/1... Batch 2380/6331... Discriminator loss: 1.4187 Generator loss: 0.7339 Epoch 0/1... Batch 2390/6331... Discriminator loss: 1.4386 Generator loss: 0.7289 Epoch 0/1... Batch 2400/6331... Discriminator loss: 1.3959 Generator loss: 0.7653
Batches: 38%|███████████████████████████▎ | 2400/6331 [05:41<08:59, 7.29batch/s]
Epoch 0/1... Batch 2410/6331... Discriminator loss: 1.3933 Generator loss: 0.8716 Epoch 0/1... Batch 2420/6331... Discriminator loss: 1.4074 Generator loss: 0.8618 Epoch 0/1... Batch 2430/6331... Discriminator loss: 1.3782 Generator loss: 0.7581 Epoch 0/1... Batch 2440/6331... Discriminator loss: 1.3948 Generator loss: 0.7745 Epoch 0/1... Batch 2450/6331... Discriminator loss: 1.3891 Generator loss: 0.8062 Epoch 0/1... Batch 2460/6331... Discriminator loss: 1.4114 Generator loss: 0.7261 Epoch 0/1... Batch 2470/6331... Discriminator loss: 1.4096 Generator loss: 0.7100 Epoch 0/1... Batch 2480/6331... Discriminator loss: 1.4456 Generator loss: 0.7886 Epoch 0/1... Batch 2490/6331... Discriminator loss: 1.3927 Generator loss: 0.8438 Epoch 0/1... Batch 2500/6331... Discriminator loss: 1.4002 Generator loss: 0.8301
Batches: 39%|████████████████████████████▍ | 2500/6331 [05:54<08:41, 7.35batch/s]
Epoch 0/1... Batch 2510/6331... Discriminator loss: 1.4181 Generator loss: 0.7746 Epoch 0/1... Batch 2520/6331... Discriminator loss: 1.3959 Generator loss: 0.8079 Epoch 0/1... Batch 2530/6331... Discriminator loss: 1.3974 Generator loss: 0.8036 Epoch 0/1... Batch 2540/6331... Discriminator loss: 1.3952 Generator loss: 0.7767 Epoch 0/1... Batch 2550/6331... Discriminator loss: 1.4342 Generator loss: 0.8019 Epoch 0/1... Batch 2560/6331... Discriminator loss: 1.3841 Generator loss: 0.7937 Epoch 0/1... Batch 2570/6331... Discriminator loss: 1.4443 Generator loss: 0.7174 Epoch 0/1... Batch 2580/6331... Discriminator loss: 1.4184 Generator loss: 0.7491 Epoch 0/1... Batch 2590/6331... Discriminator loss: 1.4369 Generator loss: 0.6690 Epoch 0/1... Batch 2600/6331... Discriminator loss: 1.3574 Generator loss: 0.7093
Batches: 41%|█████████████████████████████▌ | 2600/6331 [06:09<08:37, 7.21batch/s]
Epoch 0/1... Batch 2610/6331... Discriminator loss: 1.4188 Generator loss: 0.7466 Epoch 0/1... Batch 2620/6331... Discriminator loss: 1.3787 Generator loss: 0.7197 Epoch 0/1... Batch 2630/6331... Discriminator loss: 1.3963 Generator loss: 0.8015 Epoch 0/1... Batch 2640/6331... Discriminator loss: 1.4273 Generator loss: 0.6855 Epoch 0/1... Batch 2650/6331... Discriminator loss: 1.3967 Generator loss: 0.7379 Epoch 0/1... Batch 2660/6331... Discriminator loss: 1.3808 Generator loss: 0.8834 Epoch 0/1... Batch 2670/6331... Discriminator loss: 1.3893 Generator loss: 0.7496 Epoch 0/1... Batch 2680/6331... Discriminator loss: 1.4010 Generator loss: 0.8369 Epoch 0/1... Batch 2690/6331... Discriminator loss: 1.4212 Generator loss: 0.7447 Epoch 0/1... Batch 2700/6331... Discriminator loss: 1.3853 Generator loss: 0.7729
Batches: 43%|██████████████████████████████▋ | 2700/6331 [06:23<08:32, 7.08batch/s]
Epoch 0/1... Batch 2710/6331... Discriminator loss: 1.3650 Generator loss: 0.7843 Epoch 0/1... Batch 2720/6331... Discriminator loss: 1.4168 Generator loss: 0.7429 Epoch 0/1... Batch 2730/6331... Discriminator loss: 1.4110 Generator loss: 0.8133 Epoch 0/1... Batch 2740/6331... Discriminator loss: 1.4019 Generator loss: 0.7155 Epoch 0/1... Batch 2750/6331... Discriminator loss: 1.4140 Generator loss: 0.8374 Epoch 0/1... Batch 2760/6331... Discriminator loss: 1.3974 Generator loss: 0.8085 Epoch 0/1... Batch 2770/6331... Discriminator loss: 1.4079 Generator loss: 0.7584 Epoch 0/1... Batch 2780/6331... Discriminator loss: 1.3944 Generator loss: 0.7467 Epoch 0/1... Batch 2790/6331... Discriminator loss: 1.4266 Generator loss: 0.7280 Epoch 0/1... Batch 2800/6331... Discriminator loss: 1.4359 Generator loss: 0.6858
Batches: 44%|███████████████████████████████▊ | 2800/6331 [06:38<08:24, 7.00batch/s]
Epoch 0/1... Batch 2810/6331... Discriminator loss: 1.4575 Generator loss: 0.7500 Epoch 0/1... Batch 2820/6331... Discriminator loss: 1.4265 Generator loss: 0.7803 Epoch 0/1... Batch 2830/6331... Discriminator loss: 1.3816 Generator loss: 0.7453 Epoch 0/1... Batch 2840/6331... Discriminator loss: 1.3875 Generator loss: 0.7637 Epoch 0/1... Batch 2850/6331... Discriminator loss: 1.4063 Generator loss: 0.7916 Epoch 0/1... Batch 2860/6331... Discriminator loss: 1.3769 Generator loss: 0.8065 Epoch 0/1... Batch 2870/6331... Discriminator loss: 1.3847 Generator loss: 0.7914 Epoch 0/1... Batch 2880/6331... Discriminator loss: 1.4038 Generator loss: 0.6847 Epoch 0/1... Batch 2890/6331... Discriminator loss: 1.3950 Generator loss: 0.8328 Epoch 0/1... Batch 2900/6331... Discriminator loss: 1.4495 Generator loss: 0.7320
Batches: 46%|████████████████████████████████▉ | 2900/6331 [06:51<08:02, 7.11batch/s]
Epoch 0/1... Batch 2910/6331... Discriminator loss: 1.4024 Generator loss: 0.7592 Epoch 0/1... Batch 2920/6331... Discriminator loss: 1.4138 Generator loss: 0.7369 Epoch 0/1... Batch 2930/6331... Discriminator loss: 1.3755 Generator loss: 0.7914 Epoch 0/1... Batch 2940/6331... Discriminator loss: 1.3678 Generator loss: 0.7910 Epoch 0/1... Batch 2950/6331... Discriminator loss: 1.4036 Generator loss: 0.7912 Epoch 0/1... Batch 2960/6331... Discriminator loss: 1.4079 Generator loss: 0.7753 Epoch 0/1... Batch 2970/6331... Discriminator loss: 1.4133 Generator loss: 0.8021 Epoch 0/1... Batch 2980/6331... Discriminator loss: 1.4149 Generator loss: 0.7805 Epoch 0/1... Batch 2990/6331... Discriminator loss: 1.3890 Generator loss: 0.7564 Epoch 0/1... Batch 3000/6331... Discriminator loss: 1.3838 Generator loss: 0.8103
Batches: 47%|██████████████████████████████████ | 3000/6331 [07:05<07:45, 7.16batch/s]
Epoch 0/1... Batch 3010/6331... Discriminator loss: 1.3930 Generator loss: 0.8224 Epoch 0/1... Batch 3020/6331... Discriminator loss: 1.3934 Generator loss: 0.7287 Epoch 0/1... Batch 3030/6331... Discriminator loss: 1.3953 Generator loss: 0.7923 Epoch 0/1... Batch 3040/6331... Discriminator loss: 1.4066 Generator loss: 0.6989 Epoch 0/1... Batch 3050/6331... Discriminator loss: 1.4134 Generator loss: 0.7705 Epoch 0/1... Batch 3060/6331... Discriminator loss: 1.4163 Generator loss: 0.7505 Epoch 0/1... Batch 3070/6331... Discriminator loss: 1.3536 Generator loss: 0.7943 Epoch 0/1... Batch 3080/6331... Discriminator loss: 1.5284 Generator loss: 0.6667 Epoch 0/1... Batch 3090/6331... Discriminator loss: 1.3899 Generator loss: 0.7893 Epoch 0/1... Batch 3100/6331... Discriminator loss: 1.3922 Generator loss: 0.7653
Batches: 49%|███████████████████████████████████▎ | 3100/6331 [07:19<07:33, 7.13batch/s]
Epoch 0/1... Batch 3110/6331... Discriminator loss: 1.3852 Generator loss: 0.8031 Epoch 0/1... Batch 3120/6331... Discriminator loss: 1.4038 Generator loss: 0.7515 Epoch 0/1... Batch 3130/6331... Discriminator loss: 1.4197 Generator loss: 0.7599 Epoch 0/1... Batch 3140/6331... Discriminator loss: 1.3644 Generator loss: 0.7798 Epoch 0/1... Batch 3150/6331... Discriminator loss: 1.4132 Generator loss: 0.7939 Epoch 0/1... Batch 3160/6331... Discriminator loss: 1.3970 Generator loss: 0.7717 Epoch 0/1... Batch 3170/6331... Discriminator loss: 1.4049 Generator loss: 0.7587 Epoch 0/1... Batch 3180/6331... Discriminator loss: 1.3740 Generator loss: 0.7540 Epoch 0/1... Batch 3190/6331... Discriminator loss: 1.3715 Generator loss: 0.7550 Epoch 0/1... Batch 3200/6331... Discriminator loss: 1.4202 Generator loss: 0.7458
Batches: 51%|████████████████████████████████████▍ | 3200/6331 [07:34<07:26, 7.01batch/s]
Epoch 0/1... Batch 3210/6331... Discriminator loss: 1.4309 Generator loss: 0.7261 Epoch 0/1... Batch 3220/6331... Discriminator loss: 1.4309 Generator loss: 0.8086 Epoch 0/1... Batch 3230/6331... Discriminator loss: 1.3904 Generator loss: 0.8447 Epoch 0/1... Batch 3240/6331... Discriminator loss: 1.4118 Generator loss: 0.7486 Epoch 0/1... Batch 3250/6331... Discriminator loss: 1.3958 Generator loss: 0.7786 Epoch 0/1... Batch 3260/6331... Discriminator loss: 1.4084 Generator loss: 0.8093 Epoch 0/1... Batch 3270/6331... Discriminator loss: 1.4151 Generator loss: 0.7692 Epoch 0/1... Batch 3280/6331... Discriminator loss: 1.4094 Generator loss: 0.7338 Epoch 0/1... Batch 3290/6331... Discriminator loss: 1.3766 Generator loss: 0.7796 Epoch 0/1... Batch 3300/6331... Discriminator loss: 1.4003 Generator loss: 0.7335
Batches: 52%|█████████████████████████████████████▌ | 3300/6331 [07:48<07:09, 7.06batch/s]
Epoch 0/1... Batch 3310/6331... Discriminator loss: 1.4007 Generator loss: 0.7903 Epoch 0/1... Batch 3320/6331... Discriminator loss: 1.4241 Generator loss: 0.8072 Epoch 0/1... Batch 3330/6331... Discriminator loss: 1.4076 Generator loss: 0.7174 Epoch 0/1... Batch 3340/6331... Discriminator loss: 1.4199 Generator loss: 0.8681 Epoch 0/1... Batch 3350/6331... Discriminator loss: 1.4045 Generator loss: 0.8332 Epoch 0/1... Batch 3360/6331... Discriminator loss: 1.3827 Generator loss: 0.7247 Epoch 0/1... Batch 3370/6331... Discriminator loss: 1.4204 Generator loss: 0.7961 Epoch 0/1... Batch 3380/6331... Discriminator loss: 1.4596 Generator loss: 0.7444 Epoch 0/1... Batch 3390/6331... Discriminator loss: 1.4097 Generator loss: 0.7572 Epoch 0/1... Batch 3400/6331... Discriminator loss: 1.4062 Generator loss: 0.8402
Batches: 54%|██████████████████████████████████████▋ | 3400/6331 [08:02<06:53, 7.08batch/s]
Epoch 0/1... Batch 3410/6331... Discriminator loss: 1.3905 Generator loss: 0.7360 Epoch 0/1... Batch 3420/6331... Discriminator loss: 1.3689 Generator loss: 0.7215 Epoch 0/1... Batch 3430/6331... Discriminator loss: 1.3896 Generator loss: 0.8239 Epoch 0/1... Batch 3440/6331... Discriminator loss: 1.3831 Generator loss: 0.8028 Epoch 0/1... Batch 3450/6331... Discriminator loss: 1.3976 Generator loss: 0.7663 Epoch 0/1... Batch 3460/6331... Discriminator loss: 1.4003 Generator loss: 0.6792 Epoch 0/1... Batch 3470/6331... Discriminator loss: 1.3877 Generator loss: 0.7679 Epoch 0/1... Batch 3480/6331... Discriminator loss: 1.3868 Generator loss: 0.8377 Epoch 0/1... Batch 3490/6331... Discriminator loss: 1.3902 Generator loss: 0.7468 Epoch 0/1... Batch 3500/6331... Discriminator loss: 1.3855 Generator loss: 0.8086
Batches: 55%|███████████████████████████████████████▊ | 3500/6331 [08:17<06:43, 7.01batch/s]
Epoch 0/1... Batch 3510/6331... Discriminator loss: 1.3694 Generator loss: 0.7741 Epoch 0/1... Batch 3520/6331... Discriminator loss: 1.3843 Generator loss: 0.7417 Epoch 0/1... Batch 3530/6331... Discriminator loss: 1.3976 Generator loss: 0.7905 Epoch 0/1... Batch 3540/6331... Discriminator loss: 1.3893 Generator loss: 0.7908 Epoch 0/1... Batch 3550/6331... Discriminator loss: 1.4033 Generator loss: 0.8149 Epoch 0/1... Batch 3560/6331... Discriminator loss: 1.3945 Generator loss: 0.7592 Epoch 0/1... Batch 3570/6331... Discriminator loss: 1.3916 Generator loss: 0.8110 Epoch 0/1... Batch 3580/6331... Discriminator loss: 1.3994 Generator loss: 0.8547 Epoch 0/1... Batch 3590/6331... Discriminator loss: 1.3833 Generator loss: 0.7805 Epoch 0/1... Batch 3600/6331... Discriminator loss: 1.4150 Generator loss: 0.7798
Batches: 57%|████████████████████████████████████████▉ | 3600/6331 [08:34<06:50, 6.65batch/s]
Epoch 0/1... Batch 3610/6331... Discriminator loss: 1.4018 Generator loss: 0.7677 Epoch 0/1... Batch 3620/6331... Discriminator loss: 1.3905 Generator loss: 0.7727 Epoch 0/1... Batch 3630/6331... Discriminator loss: 1.3739 Generator loss: 0.8367 Epoch 0/1... Batch 3640/6331... Discriminator loss: 1.4030 Generator loss: 0.7064 Epoch 0/1... Batch 3650/6331... Discriminator loss: 1.3878 Generator loss: 0.8150 Epoch 0/1... Batch 3660/6331... Discriminator loss: 1.3965 Generator loss: 0.7726 Epoch 0/1... Batch 3670/6331... Discriminator loss: 1.3873 Generator loss: 0.7662 Epoch 0/1... Batch 3680/6331... Discriminator loss: 1.3982 Generator loss: 0.7384 Epoch 0/1... Batch 3690/6331... Discriminator loss: 1.4012 Generator loss: 0.7330 Epoch 0/1... Batch 3700/6331... Discriminator loss: 1.3864 Generator loss: 0.7850
Batches: 58%|██████████████████████████████████████████ | 3700/6331 [08:48<06:28, 6.78batch/s]
Epoch 0/1... Batch 3710/6331... Discriminator loss: 1.3890 Generator loss: 0.7652 Epoch 0/1... Batch 3720/6331... Discriminator loss: 1.3918 Generator loss: 0.7637 Epoch 0/1... Batch 3730/6331... Discriminator loss: 1.3902 Generator loss: 0.7938 Epoch 0/1... Batch 3740/6331... Discriminator loss: 1.3748 Generator loss: 0.7779 Epoch 0/1... Batch 3750/6331... Discriminator loss: 1.4156 Generator loss: 0.7391 Epoch 0/1... Batch 3760/6331... Discriminator loss: 1.4071 Generator loss: 0.7776 Epoch 0/1... Batch 3770/6331... Discriminator loss: 1.3967 Generator loss: 0.7679 Epoch 0/1... Batch 3780/6331... Discriminator loss: 1.3820 Generator loss: 0.7158 Epoch 0/1... Batch 3790/6331... Discriminator loss: 1.4069 Generator loss: 0.7193 Epoch 0/1... Batch 3800/6331... Discriminator loss: 1.3805 Generator loss: 0.8082
Batches: 60%|███████████████████████████████████████████▏ | 3800/6331 [09:01<06:03, 6.96batch/s]
Epoch 0/1... Batch 3810/6331... Discriminator loss: 1.4156 Generator loss: 0.7043 Epoch 0/1... Batch 3820/6331... Discriminator loss: 1.3910 Generator loss: 0.8478 Epoch 0/1... Batch 3830/6331... Discriminator loss: 1.3941 Generator loss: 0.7978 Epoch 0/1... Batch 3840/6331... Discriminator loss: 1.3981 Generator loss: 0.7361 Epoch 0/1... Batch 3850/6331... Discriminator loss: 1.4040 Generator loss: 0.7973 Epoch 0/1... Batch 3860/6331... Discriminator loss: 1.3915 Generator loss: 0.7675 Epoch 0/1... Batch 3870/6331... Discriminator loss: 1.4255 Generator loss: 0.7626 Epoch 0/1... Batch 3880/6331... Discriminator loss: 1.3881 Generator loss: 0.8276 Epoch 0/1... Batch 3890/6331... Discriminator loss: 1.3825 Generator loss: 0.8189 Epoch 0/1... Batch 3900/6331... Discriminator loss: 1.3942 Generator loss: 0.8098
Batches: 62%|████████████████████████████████████████████▎ | 3900/6331 [09:15<05:48, 6.98batch/s]
Epoch 0/1... Batch 3910/6331... Discriminator loss: 1.3777 Generator loss: 0.7455 Epoch 0/1... Batch 3920/6331... Discriminator loss: 1.3710 Generator loss: 0.7786 Epoch 0/1... Batch 3930/6331... Discriminator loss: 1.3865 Generator loss: 0.7836 Epoch 0/1... Batch 3940/6331... Discriminator loss: 1.3985 Generator loss: 0.7369 Epoch 0/1... Batch 3950/6331... Discriminator loss: 1.4192 Generator loss: 0.7885 Epoch 0/1... Batch 3960/6331... Discriminator loss: 1.3794 Generator loss: 0.8352 Epoch 0/1... Batch 3970/6331... Discriminator loss: 1.3908 Generator loss: 0.7854 Epoch 0/1... Batch 3980/6331... Discriminator loss: 1.3977 Generator loss: 0.7566 Epoch 0/1... Batch 3990/6331... Discriminator loss: 1.4005 Generator loss: 0.7953 Epoch 0/1... Batch 4000/6331... Discriminator loss: 1.3961 Generator loss: 0.7970
Batches: 63%|█████████████████████████████████████████████▍ | 4000/6331 [09:29<05:29, 7.08batch/s]
Epoch 0/1... Batch 4010/6331... Discriminator loss: 1.3941 Generator loss: 0.7761 Epoch 0/1... Batch 4020/6331... Discriminator loss: 1.3988 Generator loss: 0.7822 Epoch 0/1... Batch 4030/6331... Discriminator loss: 1.3977 Generator loss: 0.7531 Epoch 0/1... Batch 4040/6331... Discriminator loss: 1.4049 Generator loss: 0.7510 Epoch 0/1... Batch 4050/6331... Discriminator loss: 1.3824 Generator loss: 0.7951 Epoch 0/1... Batch 4060/6331... Discriminator loss: 1.3841 Generator loss: 0.7662 Epoch 0/1... Batch 4070/6331... Discriminator loss: 1.3780 Generator loss: 0.7661 Epoch 0/1... Batch 4080/6331... Discriminator loss: 1.4017 Generator loss: 0.7698 Epoch 0/1... Batch 4090/6331... Discriminator loss: 1.3752 Generator loss: 0.7662 Epoch 0/1... Batch 4100/6331... Discriminator loss: 1.3778 Generator loss: 0.7535
Batches: 65%|██████████████████████████████████████████████▋ | 4100/6331 [09:43<05:12, 7.14batch/s]
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Epoch 0/1... Batch 4210/6331... Discriminator loss: 1.3880 Generator loss: 0.7484 Epoch 0/1... Batch 4220/6331... Discriminator loss: 1.3875 Generator loss: 0.8124 Epoch 0/1... Batch 4230/6331... Discriminator loss: 1.3858 Generator loss: 0.8030 Epoch 0/1... Batch 4240/6331... Discriminator loss: 1.3955 Generator loss: 0.8077 Epoch 0/1... Batch 4250/6331... Discriminator loss: 1.3963 Generator loss: 0.8587 Epoch 0/1... Batch 4260/6331... Discriminator loss: 1.3796 Generator loss: 0.8413 Epoch 0/1... Batch 4270/6331... Discriminator loss: 1.3826 Generator loss: 0.8004 Epoch 0/1... Batch 4280/6331... Discriminator loss: 1.3759 Generator loss: 0.7739 Epoch 0/1... Batch 4290/6331... Discriminator loss: 1.3969 Generator loss: 0.7925 Epoch 0/1... Batch 4300/6331... Discriminator loss: 1.3978 Generator loss: 0.7999
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Epoch 0/1... Batch 4310/6331... Discriminator loss: 1.3910 Generator loss: 0.8039 Epoch 0/1... Batch 4320/6331... Discriminator loss: 1.3917 Generator loss: 0.7618 Epoch 0/1... Batch 4330/6331... Discriminator loss: 1.3994 Generator loss: 0.7834 Epoch 0/1... Batch 4340/6331... Discriminator loss: 1.3835 Generator loss: 0.7768 Epoch 0/1... Batch 4350/6331... Discriminator loss: 1.4101 Generator loss: 0.7954 Epoch 0/1... Batch 4360/6331... Discriminator loss: 1.4127 Generator loss: 0.6996 Epoch 0/1... Batch 4370/6331... Discriminator loss: 1.3932 Generator loss: 0.7137 Epoch 0/1... Batch 4380/6331... Discriminator loss: 1.4103 Generator loss: 0.7313 Epoch 0/1... Batch 4390/6331... Discriminator loss: 1.3776 Generator loss: 0.7753 Epoch 0/1... Batch 4400/6331... Discriminator loss: 1.3902 Generator loss: 0.7983
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Epoch 0/1... Batch 4410/6331... Discriminator loss: 1.4041 Generator loss: 0.8553 Epoch 0/1... Batch 4420/6331... Discriminator loss: 1.3932 Generator loss: 0.7284 Epoch 0/1... Batch 4430/6331... Discriminator loss: 1.3896 Generator loss: 0.7327 Epoch 0/1... Batch 4440/6331... Discriminator loss: 1.3917 Generator loss: 0.7993 Epoch 0/1... Batch 4450/6331... Discriminator loss: 1.3897 Generator loss: 0.8033 Epoch 0/1... Batch 4460/6331... Discriminator loss: 1.3883 Generator loss: 0.8135 Epoch 0/1... Batch 4470/6331... Discriminator loss: 1.3966 Generator loss: 0.7667 Epoch 0/1... Batch 4480/6331... Discriminator loss: 1.3921 Generator loss: 0.7529 Epoch 0/1... Batch 4490/6331... Discriminator loss: 1.3857 Generator loss: 0.7641 Epoch 0/1... Batch 4500/6331... Discriminator loss: 1.3979 Generator loss: 0.7200
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Epoch 0/1... Batch 4510/6331... Discriminator loss: 1.3815 Generator loss: 0.8144 Epoch 0/1... Batch 4520/6331... Discriminator loss: 1.3894 Generator loss: 0.8020 Epoch 0/1... Batch 4530/6331... Discriminator loss: 1.3966 Generator loss: 0.7688 Epoch 0/1... Batch 4540/6331... Discriminator loss: 1.3912 Generator loss: 0.8110 Epoch 0/1... Batch 4550/6331... Discriminator loss: 1.3883 Generator loss: 0.7978 Epoch 0/1... Batch 4560/6331... Discriminator loss: 1.3993 Generator loss: 0.7899 Epoch 0/1... Batch 4570/6331... Discriminator loss: 1.3830 Generator loss: 0.8483 Epoch 0/1... Batch 4580/6331... Discriminator loss: 1.3954 Generator loss: 0.7946 Epoch 0/1... Batch 4590/6331... Discriminator loss: 1.3813 Generator loss: 0.8360 Epoch 0/1... Batch 4600/6331... Discriminator loss: 1.3948 Generator loss: 0.7816
Batches: 73%|████████████████████████████████████████████████████▎ | 4600/6331 [10:55<04:09, 6.94batch/s]
Epoch 0/1... Batch 4610/6331... Discriminator loss: 1.3928 Generator loss: 0.7924 Epoch 0/1... Batch 4620/6331... Discriminator loss: 1.3832 Generator loss: 0.7535 Epoch 0/1... Batch 4630/6331... Discriminator loss: 1.3833 Generator loss: 0.8122 Epoch 0/1... Batch 4640/6331... Discriminator loss: 1.3926 Generator loss: 0.7678 Epoch 0/1... Batch 4650/6331... Discriminator loss: 1.3832 Generator loss: 0.8114 Epoch 0/1... Batch 4660/6331... Discriminator loss: 1.3783 Generator loss: 0.7841 Epoch 0/1... Batch 4670/6331... Discriminator loss: 1.3743 Generator loss: 0.8621 Epoch 0/1... Batch 4680/6331... Discriminator loss: 1.3987 Generator loss: 0.7272 Epoch 0/1... Batch 4690/6331... Discriminator loss: 1.3980 Generator loss: 0.8094 Epoch 0/1... Batch 4700/6331... Discriminator loss: 1.3879 Generator loss: 0.7874
Batches: 74%|█████████████████████████████████████████████████████▍ | 4700/6331 [11:09<03:53, 6.98batch/s]
Epoch 0/1... Batch 4710/6331... Discriminator loss: 1.3810 Generator loss: 0.8247 Epoch 0/1... Batch 4720/6331... Discriminator loss: 1.3859 Generator loss: 0.8513 Epoch 0/1... Batch 4730/6331... Discriminator loss: 1.3958 Generator loss: 0.7665 Epoch 0/1... Batch 4740/6331... Discriminator loss: 1.4074 Generator loss: 0.7231 Epoch 0/1... Batch 4750/6331... Discriminator loss: 1.3857 Generator loss: 0.8048 Epoch 0/1... Batch 4760/6331... Discriminator loss: 1.3795 Generator loss: 0.7783 Epoch 0/1... Batch 4770/6331... Discriminator loss: 1.3805 Generator loss: 0.8120 Epoch 0/1... Batch 4780/6331... Discriminator loss: 1.3937 Generator loss: 0.7960 Epoch 0/1... Batch 4790/6331... Discriminator loss: 1.3831 Generator loss: 0.7954 Epoch 0/1... Batch 4800/6331... Discriminator loss: 1.3837 Generator loss: 0.8049
Batches: 76%|██████████████████████████████████████████████████████▌ | 4800/6331 [11:22<03:35, 7.11batch/s]
Epoch 0/1... Batch 4810/6331... Discriminator loss: 1.3884 Generator loss: 0.7462 Epoch 0/1... Batch 4820/6331... Discriminator loss: 1.3809 Generator loss: 0.7793 Epoch 0/1... Batch 4830/6331... Discriminator loss: 1.3926 Generator loss: 0.8449 Epoch 0/1... Batch 4840/6331... Discriminator loss: 1.3800 Generator loss: 0.7990 Epoch 0/1... Batch 4850/6331... Discriminator loss: 1.3895 Generator loss: 0.7953 Epoch 0/1... Batch 4860/6331... Discriminator loss: 1.3940 Generator loss: 0.7607 Epoch 0/1... Batch 4870/6331... Discriminator loss: 1.3896 Generator loss: 0.8083 Epoch 0/1... Batch 4880/6331... Discriminator loss: 1.3814 Generator loss: 0.7908 Epoch 0/1... Batch 4890/6331... Discriminator loss: 1.3823 Generator loss: 0.7868 Epoch 0/1... Batch 4900/6331... Discriminator loss: 1.3887 Generator loss: 0.7834
Batches: 77%|███████████████████████████████████████████████████████▋ | 4900/6331 [11:37<03:22, 7.06batch/s]
Epoch 0/1... Batch 4910/6331... Discriminator loss: 1.3842 Generator loss: 0.8061 Epoch 0/1... Batch 4920/6331... Discriminator loss: 1.3847 Generator loss: 0.8213 Epoch 0/1... Batch 4930/6331... Discriminator loss: 1.3936 Generator loss: 0.7937 Epoch 0/1... Batch 4940/6331... Discriminator loss: 1.3767 Generator loss: 0.7764 Epoch 0/1... Batch 4950/6331... Discriminator loss: 1.3800 Generator loss: 0.8302 Epoch 0/1... Batch 4960/6331... Discriminator loss: 1.3798 Generator loss: 0.8466 Epoch 0/1... Batch 4970/6331... Discriminator loss: 1.3790 Generator loss: 0.8353 Epoch 0/1... Batch 4980/6331... Discriminator loss: 1.3863 Generator loss: 0.8039 Epoch 0/1... Batch 4990/6331... Discriminator loss: 1.3831 Generator loss: 0.7635 Epoch 0/1... Batch 5000/6331... Discriminator loss: 1.3847 Generator loss: 0.7980
Batches: 79%|████████████████████████████████████████████████████████▊ | 5000/6331 [11:51<03:09, 7.03batch/s]
Epoch 0/1... Batch 5010/6331... Discriminator loss: 1.3797 Generator loss: 0.7707 Epoch 0/1... Batch 5020/6331... Discriminator loss: 1.3809 Generator loss: 0.7975 Epoch 0/1... Batch 5030/6331... Discriminator loss: 1.3982 Generator loss: 0.7555 Epoch 0/1... Batch 5040/6331... Discriminator loss: 1.3984 Generator loss: 0.7511 Epoch 0/1... Batch 5050/6331... Discriminator loss: 1.3848 Generator loss: 0.7793 Epoch 0/1... Batch 5060/6331... Discriminator loss: 1.3824 Generator loss: 0.7802 Epoch 0/1... Batch 5070/6331... Discriminator loss: 1.4280 Generator loss: 0.8145 Epoch 0/1... Batch 5080/6331... Discriminator loss: 1.4141 Generator loss: 0.7457 Epoch 0/1... Batch 5090/6331... Discriminator loss: 1.3787 Generator loss: 0.7506 Epoch 0/1... Batch 5100/6331... Discriminator loss: 1.3983 Generator loss: 0.7918
Batches: 81%|██████████████████████████████████████████████████████████ | 5100/6331 [12:05<02:52, 7.12batch/s]
Epoch 0/1... Batch 5110/6331... Discriminator loss: 1.3909 Generator loss: 0.7732 Epoch 0/1... Batch 5120/6331... Discriminator loss: 1.3856 Generator loss: 0.7842 Epoch 0/1... Batch 5130/6331... Discriminator loss: 1.3899 Generator loss: 0.7663 Epoch 0/1... Batch 5140/6331... Discriminator loss: 1.3825 Generator loss: 0.7598 Epoch 0/1... Batch 5150/6331... Discriminator loss: 1.3878 Generator loss: 0.8423 Epoch 0/1... Batch 5160/6331... Discriminator loss: 1.3838 Generator loss: 0.8178 Epoch 0/1... Batch 5170/6331... Discriminator loss: 1.4015 Generator loss: 0.7660 Epoch 0/1... Batch 5180/6331... Discriminator loss: 1.3818 Generator loss: 0.8228 Epoch 0/1... Batch 5190/6331... Discriminator loss: 1.3905 Generator loss: 0.7688 Epoch 0/1... Batch 5200/6331... Discriminator loss: 1.3866 Generator loss: 0.7983
Batches: 82%|███████████████████████████████████████████████████████████▏ | 5200/6331 [12:22<02:51, 6.61batch/s]
Epoch 0/1... Batch 5210/6331... Discriminator loss: 1.3775 Generator loss: 0.8025 Epoch 0/1... Batch 5220/6331... Discriminator loss: 1.3825 Generator loss: 0.8375 Epoch 0/1... Batch 5230/6331... Discriminator loss: 1.3840 Generator loss: 0.7990 Epoch 0/1... Batch 5240/6331... Discriminator loss: 1.3838 Generator loss: 0.8105 Epoch 0/1... Batch 5250/6331... Discriminator loss: 1.3906 Generator loss: 0.7816 Epoch 0/1... Batch 5260/6331... Discriminator loss: 1.3974 Generator loss: 0.7476 Epoch 0/1... Batch 5270/6331... Discriminator loss: 1.3804 Generator loss: 0.7728 Epoch 0/1... Batch 5280/6331... Discriminator loss: 1.4006 Generator loss: 0.7682 Epoch 0/1... Batch 5290/6331... Discriminator loss: 1.3900 Generator loss: 0.7765 Epoch 0/1... Batch 5300/6331... Discriminator loss: 1.3777 Generator loss: 0.7241
Batches: 84%|████████████████████████████████████████████████████████████▎ | 5300/6331 [12:39<02:42, 6.36batch/s]
Epoch 0/1... Batch 5310/6331... Discriminator loss: 1.3991 Generator loss: 0.7314 Epoch 0/1... Batch 5320/6331... Discriminator loss: 1.3940 Generator loss: 0.7322 Epoch 0/1... Batch 5330/6331... Discriminator loss: 1.3828 Generator loss: 0.8299 Epoch 0/1... Batch 5340/6331... Discriminator loss: 1.3787 Generator loss: 0.7853 Epoch 0/1... Batch 5350/6331... Discriminator loss: 1.4015 Generator loss: 0.7847 Epoch 0/1... Batch 5360/6331... Discriminator loss: 1.3833 Generator loss: 0.8119 Epoch 0/1... Batch 5370/6331... Discriminator loss: 1.3763 Generator loss: 0.8122 Epoch 0/1... Batch 5380/6331... Discriminator loss: 1.3938 Generator loss: 0.7871 Epoch 0/1... Batch 5390/6331... Discriminator loss: 1.3768 Generator loss: 0.7658 Epoch 0/1... Batch 5400/6331... Discriminator loss: 1.3809 Generator loss: 0.8307
Batches: 85%|█████████████████████████████████████████████████████████████▍ | 5400/6331 [12:53<02:19, 6.67batch/s]
Epoch 0/1... Batch 5410/6331... Discriminator loss: 1.3722 Generator loss: 0.7725 Epoch 0/1... Batch 5420/6331... Discriminator loss: 1.3981 Generator loss: 0.7663 Epoch 0/1... Batch 5430/6331... Discriminator loss: 1.3819 Generator loss: 0.7800 Epoch 0/1... Batch 5440/6331... Discriminator loss: 1.3826 Generator loss: 0.8005 Epoch 0/1... Batch 5450/6331... Discriminator loss: 1.3812 Generator loss: 0.8139 Epoch 0/1... Batch 5460/6331... Discriminator loss: 1.3836 Generator loss: 0.7999 Epoch 0/1... Batch 5470/6331... Discriminator loss: 1.3784 Generator loss: 0.8460 Epoch 0/1... Batch 5480/6331... Discriminator loss: 1.3886 Generator loss: 0.7600 Epoch 0/1... Batch 5490/6331... Discriminator loss: 1.4140 Generator loss: 0.7379 Epoch 0/1... Batch 5500/6331... Discriminator loss: 1.3885 Generator loss: 0.7914
Batches: 87%|██████████████████████████████████████████████████████████████▌ | 5500/6331 [13:07<02:02, 6.81batch/s]
Epoch 0/1... Batch 5510/6331... Discriminator loss: 1.3807 Generator loss: 0.7756 Epoch 0/1... Batch 5520/6331... Discriminator loss: 1.3834 Generator loss: 0.7703 Epoch 0/1... Batch 5530/6331... Discriminator loss: 1.3869 Generator loss: 0.7704 Epoch 0/1... Batch 5540/6331... Discriminator loss: 1.3894 Generator loss: 0.8252 Epoch 0/1... Batch 5550/6331... Discriminator loss: 1.3767 Generator loss: 0.7625 Epoch 0/1... Batch 5560/6331... Discriminator loss: 1.3848 Generator loss: 0.7781 Epoch 0/1... Batch 5570/6331... Discriminator loss: 1.3826 Generator loss: 0.8106 Epoch 0/1... Batch 5580/6331... Discriminator loss: 1.3737 Generator loss: 0.7704 Epoch 0/1... Batch 5590/6331... Discriminator loss: 1.3865 Generator loss: 0.7926 Epoch 0/1... Batch 5600/6331... Discriminator loss: 1.3805 Generator loss: 0.8043
Batches: 88%|███████████████████████████████████████████████████████████████▋ | 5600/6331 [13:21<01:45, 6.92batch/s]
Epoch 0/1... Batch 5610/6331... Discriminator loss: 1.3864 Generator loss: 0.8141 Epoch 0/1... Batch 5620/6331... Discriminator loss: 1.3740 Generator loss: 0.7878 Epoch 0/1... Batch 5630/6331... Discriminator loss: 1.3829 Generator loss: 0.7674 Epoch 0/1... Batch 5640/6331... Discriminator loss: 1.3819 Generator loss: 0.8129 Epoch 0/1... Batch 5650/6331... Discriminator loss: 1.3802 Generator loss: 0.7964 Epoch 0/1... Batch 5660/6331... Discriminator loss: 1.3799 Generator loss: 0.7770 Epoch 0/1... Batch 5670/6331... Discriminator loss: 1.3768 Generator loss: 0.7632 Epoch 0/1... Batch 5680/6331... Discriminator loss: 1.3887 Generator loss: 0.7461 Epoch 0/1... Batch 5690/6331... Discriminator loss: 1.3816 Generator loss: 0.8004 Epoch 0/1... Batch 5700/6331... Discriminator loss: 1.3889 Generator loss: 0.7914
Batches: 90%|████████████████████████████████████████████████████████████████▊ | 5700/6331 [13:35<01:30, 7.00batch/s]
Epoch 0/1... Batch 5710/6331... Discriminator loss: 1.3857 Generator loss: 0.7949 Epoch 0/1... Batch 5720/6331... Discriminator loss: 1.3753 Generator loss: 0.7758 Epoch 0/1... Batch 5730/6331... Discriminator loss: 1.3795 Generator loss: 0.7870 Epoch 0/1... Batch 5740/6331... Discriminator loss: 1.3827 Generator loss: 0.8093 Epoch 0/1... Batch 5750/6331... Discriminator loss: 1.3802 Generator loss: 0.7920 Epoch 0/1... Batch 5760/6331... Discriminator loss: 1.3915 Generator loss: 0.7412 Epoch 0/1... Batch 5770/6331... Discriminator loss: 1.3856 Generator loss: 0.7797 Epoch 0/1... Batch 5780/6331... Discriminator loss: 1.3858 Generator loss: 0.7766 Epoch 0/1... Batch 5790/6331... Discriminator loss: 1.3807 Generator loss: 0.8100 Epoch 0/1... Batch 5800/6331... Discriminator loss: 1.3822 Generator loss: 0.7926
Batches: 92%|█████████████████████████████████████████████████████████████████▉ | 5800/6331 [13:48<01:14, 7.12batch/s]
Epoch 0/1... Batch 5810/6331... Discriminator loss: 1.3774 Generator loss: 0.8032 Epoch 0/1... Batch 5820/6331... Discriminator loss: 1.3911 Generator loss: 0.7952 Epoch 0/1... Batch 5830/6331... Discriminator loss: 1.3820 Generator loss: 0.7841 Epoch 0/1... Batch 5840/6331... Discriminator loss: 1.3955 Generator loss: 0.8000 Epoch 0/1... Batch 5850/6331... Discriminator loss: 1.3757 Generator loss: 0.7693 Epoch 0/1... Batch 5860/6331... Discriminator loss: 1.3777 Generator loss: 0.7946 Epoch 0/1... Batch 5870/6331... Discriminator loss: 1.3788 Generator loss: 0.8241 Epoch 0/1... Batch 5880/6331... Discriminator loss: 1.3861 Generator loss: 0.7736 Epoch 0/1... Batch 5890/6331... Discriminator loss: 1.3886 Generator loss: 0.8349 Epoch 0/1... Batch 5900/6331... Discriminator loss: 1.3784 Generator loss: 0.8161
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Epoch 0/1... Batch 5910/6331... Discriminator loss: 1.3886 Generator loss: 0.7604 Epoch 0/1... Batch 5920/6331... Discriminator loss: 1.3908 Generator loss: 0.7743 Epoch 0/1... Batch 5930/6331... Discriminator loss: 1.3764 Generator loss: 0.8068 Epoch 0/1... Batch 5940/6331... Discriminator loss: 1.3834 Generator loss: 0.8251 Epoch 0/1... Batch 5950/6331... Discriminator loss: 1.3810 Generator loss: 0.7784 Epoch 0/1... Batch 5960/6331... Discriminator loss: 1.3804 Generator loss: 0.8115 Epoch 0/1... Batch 5970/6331... Discriminator loss: 1.3803 Generator loss: 0.8105 Epoch 0/1... Batch 5980/6331... Discriminator loss: 1.3814 Generator loss: 0.8038 Epoch 0/1... Batch 5990/6331... Discriminator loss: 1.3864 Generator loss: 0.7633 Epoch 0/1... Batch 6000/6331... Discriminator loss: 1.3810 Generator loss: 0.7853
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Epoch 0/1... Batch 6010/6331... Discriminator loss: 1.3822 Generator loss: 0.7621 Epoch 0/1... Batch 6020/6331... Discriminator loss: 1.3783 Generator loss: 0.7884 Epoch 0/1... Batch 6030/6331... Discriminator loss: 1.3806 Generator loss: 0.8105 Epoch 0/1... Batch 6040/6331... Discriminator loss: 1.3842 Generator loss: 0.7888 Epoch 0/1... Batch 6050/6331... Discriminator loss: 1.3902 Generator loss: 0.7795 Epoch 0/1... Batch 6060/6331... Discriminator loss: 1.3846 Generator loss: 0.7342 Epoch 0/1... Batch 6070/6331... Discriminator loss: 1.3891 Generator loss: 0.7934 Epoch 0/1... Batch 6080/6331... Discriminator loss: 1.3813 Generator loss: 0.7971 Epoch 0/1... Batch 6090/6331... Discriminator loss: 1.3814 Generator loss: 0.8024 Epoch 0/1... Batch 6100/6331... Discriminator loss: 1.3859 Generator loss: 0.7973
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Epoch 0/1... Batch 6110/6331... Discriminator loss: 1.3799 Generator loss: 0.7836 Epoch 0/1... Batch 6120/6331... Discriminator loss: 1.3919 Generator loss: 0.8200 Epoch 0/1... Batch 6130/6331... Discriminator loss: 1.3857 Generator loss: 0.7847 Epoch 0/1... Batch 6140/6331... Discriminator loss: 1.3788 Generator loss: 0.7935 Epoch 0/1... Batch 6150/6331... Discriminator loss: 1.3809 Generator loss: 0.7719 Epoch 0/1... Batch 6160/6331... Discriminator loss: 1.3923 Generator loss: 0.7756 Epoch 0/1... Batch 6170/6331... Discriminator loss: 1.3854 Generator loss: 0.7348 Epoch 0/1... Batch 6180/6331... Discriminator loss: 1.3812 Generator loss: 0.8104 Epoch 0/1... Batch 6190/6331... Discriminator loss: 1.3834 Generator loss: 0.7891 Epoch 0/1... Batch 6200/6331... Discriminator loss: 1.3778 Generator loss: 0.8395
Batches: 98%|██████████████████████████████████████████████████████████████████████▌ | 6200/6331 [14:45<00:18, 7.06batch/s]
Epoch 0/1... Batch 6210/6331... Discriminator loss: 1.3830 Generator loss: 0.7872 Epoch 0/1... Batch 6220/6331... Discriminator loss: 1.3848 Generator loss: 0.7984 Epoch 0/1... Batch 6230/6331... Discriminator loss: 1.3938 Generator loss: 0.7494 Epoch 0/1... Batch 6240/6331... Discriminator loss: 1.3821 Generator loss: 0.8132 Epoch 0/1... Batch 6250/6331... Discriminator loss: 1.3824 Generator loss: 0.7746 Epoch 0/1... Batch 6260/6331... Discriminator loss: 1.3856 Generator loss: 0.7712 Epoch 0/1... Batch 6270/6331... Discriminator loss: 1.3856 Generator loss: 0.8516 Epoch 0/1... Batch 6280/6331... Discriminator loss: 1.3829 Generator loss: 0.8427 Epoch 0/1... Batch 6290/6331... Discriminator loss: 1.3771 Generator loss: 0.8055 Epoch 0/1... Batch 6300/6331... Discriminator loss: 1.3795 Generator loss: 0.7853
Batches: 100%|███████████████████████████████████████████████████████████████████████▋| 6300/6331 [15:00<00:04, 6.91batch/s]
Epoch 0/1... Batch 6310/6331... Discriminator loss: 1.3818 Generator loss: 0.7901 Epoch 0/1... Batch 6320/6331... Discriminator loss: 1.3860 Generator loss: 0.7909 Epoch 0/1... Batch 6330/6331... Discriminator loss: 1.3785 Generator loss: 0.7834
Epochs: 100%|██████████████████████████████████████████████████████████████████████████████| 1/1 [15:04<00:00, 904.21s/epoch]
batch_size = 32
z_dim = 200
learning_rate = 0.01 # too high
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
batch_size = 32
z_dim = 200
learning_rate = 0.004 # too high
beta1 = 0.5
alpha = 0.2
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode, alpha)
z_dim = 200
beta1 = 0.5
# Generate some random faces
def generate_faces(checkpoint=None, z_dim=z_dim, beta1=beta1, show_n_images=25):
graph = tf.Graph()
if not checkpoint:
checkpoint = tf.train.latest_checkpoint('checkpoints')
print('Generating faces from saved checkpoint:', checkpoint)
with graph.as_default():
input_real, input_z, learn_rate = model_inputs(28, 28, 3, z_dim)
d_loss, g_loss = model_loss(input_real, input_z, 3)
d_opt, g_opt = model_opt(d_loss, g_loss, learn_rate, beta1)
#dummy = tf.Variable(0)
saver = tf.train.Saver()
with tf.Session() as sess:
#sess.run(tf.global_variables_initializer())
saver.restore(sess, checkpoint)
show_generator_output(sess, show_n_images, input_z, 3, 'RGB')
generate_faces()
Generating faces from saved checkpoint: checkpoints\generator_bs32_zd200_lr0.002_b0.3.ckpt
generate_faces(show_n_images=16)
Generating faces from saved checkpoint: checkpoints\generator_bs32_zd200_lr0.002_b0.3.ckpt
So far the hyperparameters that give better looking visuals
batch_size = 32
z_dim = 200
learning_rate = 0.002
beta1 = 0.5
alpha = 0.2
generate_faces('checkpoints\generator_bs32_zd200_lr0.002_b0.5.ckpt')
Generating faces from saved checkpoint: checkpoints\generator_bs32_zd200_lr0.002_b0.5.ckpt
generate_faces('checkpoints\generator_bs32_zd200_lr0.002_b0.5.ckpt', show_n_images=16)
Generating faces from saved checkpoint: checkpoints\generator_bs32_zd200_lr0.002_b0.5.ckpt
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.